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Unpacking polarization: Antagonism and Alignment in Signed Networks of Online Interaction

Published 13 Jul 2023 in cs.SI and cs.CY | (2307.06571v3)

Abstract: Political conflict is an essential element of democratic systems, but can also threaten their existence if it becomes too intense. This happens particularly when most political issues become aligned along the same major fault line, splitting society into two antagonistic camps. In the 20th century, major fault lines were formed by structural conflicts, like owners vs workers, center vs periphery, etc. But these classical cleavages have since lost their explanatory power. Instead of theorizing new cleavages, we present the FAULTANA (FAULT-line Alignment Network Analysis) pipeline, a computational method to uncover major fault lines in data of signed online interactions. Our method makes it possible to quantify the degree of antagonism prevalent in different online debates, as well as how aligned each debate is to the major fault line. This makes it possible to identify the wedge issues driving polarization, characterized by both intense antagonism and alignment. We apply our approach to large-scale data sets of Birdwatch, a US-based Twitter fact-checking community and the discussion forums of DerStandard, an Austrian online newspaper. We find that both online communities are divided into two large groups and that their separation follows political identities and topics. In addition, for DerStandard, we pinpoint issues that reinforce societal fault lines and thus drive polarization. We also identify issues that trigger online conflict without strictly aligning with those dividing lines (e.g. COVID-19). Our methods allow us to construct a time-resolved picture of affective polarization that shows the separate contributions of cohesiveness and divisiveness to the dynamics of alignment during contentious elections and events.

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References (53)
  1. Rokkan, S.: Geography, religion, and social class: Crosscutting cleavages in norwegian politics. Party systems and voter alignments 367, 379–86 (1967) Blau and Schwartz [1984] Blau, P.M., Schwartz, J.E.: Crosscutting social circles: Testing a macrostructural theory of intergroup relations (1984) Mason [2016] Mason, L.: A cross-cutting calm: How social sorting drives affective polarization. Public Opinion Quarterly 80(S1), 351–377 (2016) Finkel et al. [2020] Finkel, E.J., Bail, C.A., Cikara, M., Ditto, P.H., Iyengar, S., Klar, S., Mason, L., McGrath, M.C., Nyhan, B., Rand, D.G., et al.: Political sectarianism in america. Science 370(6516), 533–536 (2020) Lipset et al. [1967] Lipset, S.M., Lipset, S.M., Rokkan, S.: Party Systems and Voter Alignments: Cross-national Perspectives vol. 7. New York: Free Press, ??? (1967) Franklin [1992] Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Blau, P.M., Schwartz, J.E.: Crosscutting social circles: Testing a macrostructural theory of intergroup relations (1984) Mason [2016] Mason, L.: A cross-cutting calm: How social sorting drives affective polarization. Public Opinion Quarterly 80(S1), 351–377 (2016) Finkel et al. [2020] Finkel, E.J., Bail, C.A., Cikara, M., Ditto, P.H., Iyengar, S., Klar, S., Mason, L., McGrath, M.C., Nyhan, B., Rand, D.G., et al.: Political sectarianism in america. Science 370(6516), 533–536 (2020) Lipset et al. [1967] Lipset, S.M., Lipset, S.M., Rokkan, S.: Party Systems and Voter Alignments: Cross-national Perspectives vol. 7. New York: Free Press, ??? (1967) Franklin [1992] Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Mason, L.: A cross-cutting calm: How social sorting drives affective polarization. Public Opinion Quarterly 80(S1), 351–377 (2016) Finkel et al. [2020] Finkel, E.J., Bail, C.A., Cikara, M., Ditto, P.H., Iyengar, S., Klar, S., Mason, L., McGrath, M.C., Nyhan, B., Rand, D.G., et al.: Political sectarianism in america. Science 370(6516), 533–536 (2020) Lipset et al. [1967] Lipset, S.M., Lipset, S.M., Rokkan, S.: Party Systems and Voter Alignments: Cross-national Perspectives vol. 7. New York: Free Press, ??? (1967) Franklin [1992] Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Finkel, E.J., Bail, C.A., Cikara, M., Ditto, P.H., Iyengar, S., Klar, S., Mason, L., McGrath, M.C., Nyhan, B., Rand, D.G., et al.: Political sectarianism in america. Science 370(6516), 533–536 (2020) Lipset et al. [1967] Lipset, S.M., Lipset, S.M., Rokkan, S.: Party Systems and Voter Alignments: Cross-national Perspectives vol. 7. New York: Free Press, ??? (1967) Franklin [1992] Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Lipset, S.M., Lipset, S.M., Rokkan, S.: Party Systems and Voter Alignments: Cross-national Perspectives vol. 7. New York: Free Press, ??? (1967) Franklin [1992] Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  2. Blau, P.M., Schwartz, J.E.: Crosscutting social circles: Testing a macrostructural theory of intergroup relations (1984) Mason [2016] Mason, L.: A cross-cutting calm: How social sorting drives affective polarization. Public Opinion Quarterly 80(S1), 351–377 (2016) Finkel et al. [2020] Finkel, E.J., Bail, C.A., Cikara, M., Ditto, P.H., Iyengar, S., Klar, S., Mason, L., McGrath, M.C., Nyhan, B., Rand, D.G., et al.: Political sectarianism in america. Science 370(6516), 533–536 (2020) Lipset et al. [1967] Lipset, S.M., Lipset, S.M., Rokkan, S.: Party Systems and Voter Alignments: Cross-national Perspectives vol. 7. New York: Free Press, ??? (1967) Franklin [1992] Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Mason, L.: A cross-cutting calm: How social sorting drives affective polarization. Public Opinion Quarterly 80(S1), 351–377 (2016) Finkel et al. [2020] Finkel, E.J., Bail, C.A., Cikara, M., Ditto, P.H., Iyengar, S., Klar, S., Mason, L., McGrath, M.C., Nyhan, B., Rand, D.G., et al.: Political sectarianism in america. Science 370(6516), 533–536 (2020) Lipset et al. [1967] Lipset, S.M., Lipset, S.M., Rokkan, S.: Party Systems and Voter Alignments: Cross-national Perspectives vol. 7. New York: Free Press, ??? (1967) Franklin [1992] Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Finkel, E.J., Bail, C.A., Cikara, M., Ditto, P.H., Iyengar, S., Klar, S., Mason, L., McGrath, M.C., Nyhan, B., Rand, D.G., et al.: Political sectarianism in america. Science 370(6516), 533–536 (2020) Lipset et al. [1967] Lipset, S.M., Lipset, S.M., Rokkan, S.: Party Systems and Voter Alignments: Cross-national Perspectives vol. 7. New York: Free Press, ??? (1967) Franklin [1992] Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Lipset, S.M., Lipset, S.M., Rokkan, S.: Party Systems and Voter Alignments: Cross-national Perspectives vol. 7. New York: Free Press, ??? (1967) Franklin [1992] Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  3. Mason, L.: A cross-cutting calm: How social sorting drives affective polarization. Public Opinion Quarterly 80(S1), 351–377 (2016) Finkel et al. [2020] Finkel, E.J., Bail, C.A., Cikara, M., Ditto, P.H., Iyengar, S., Klar, S., Mason, L., McGrath, M.C., Nyhan, B., Rand, D.G., et al.: Political sectarianism in america. Science 370(6516), 533–536 (2020) Lipset et al. [1967] Lipset, S.M., Lipset, S.M., Rokkan, S.: Party Systems and Voter Alignments: Cross-national Perspectives vol. 7. New York: Free Press, ??? (1967) Franklin [1992] Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Finkel, E.J., Bail, C.A., Cikara, M., Ditto, P.H., Iyengar, S., Klar, S., Mason, L., McGrath, M.C., Nyhan, B., Rand, D.G., et al.: Political sectarianism in america. Science 370(6516), 533–536 (2020) Lipset et al. [1967] Lipset, S.M., Lipset, S.M., Rokkan, S.: Party Systems and Voter Alignments: Cross-national Perspectives vol. 7. New York: Free Press, ??? (1967) Franklin [1992] Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Lipset, S.M., Lipset, S.M., Rokkan, S.: Party Systems and Voter Alignments: Cross-national Perspectives vol. 7. New York: Free Press, ??? (1967) Franklin [1992] Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  4. Finkel, E.J., Bail, C.A., Cikara, M., Ditto, P.H., Iyengar, S., Klar, S., Mason, L., McGrath, M.C., Nyhan, B., Rand, D.G., et al.: Political sectarianism in america. Science 370(6516), 533–536 (2020) Lipset et al. [1967] Lipset, S.M., Lipset, S.M., Rokkan, S.: Party Systems and Voter Alignments: Cross-national Perspectives vol. 7. New York: Free Press, ??? (1967) Franklin [1992] Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Lipset, S.M., Lipset, S.M., Rokkan, S.: Party Systems and Voter Alignments: Cross-national Perspectives vol. 7. New York: Free Press, ??? (1967) Franklin [1992] Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  5. Lipset, S.M., Lipset, S.M., Rokkan, S.: Party Systems and Voter Alignments: Cross-national Perspectives vol. 7. New York: Free Press, ??? (1967) Franklin [1992] Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  6. Franklin, M.N.: The decline of cleavage politics. Electoral change: Responses to evolving social and attitudinal structures in Western countries, 383–405 (1992) Kriesi et al. [2008] Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  7. Kriesi, H., Grande, E., Lachat, R., Dolezal, M., Bornschier, S., Frey, T.: West European Politics in the Age of Globalization. Cambridge University Press, ??? (2008) Ford and Jennings [2020] Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  8. Ford, R., Jennings, W.: The changing cleavage politics of western europe. Annual review of political science 23, 295–314 (2020) Hooghe and Marks [2018] Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  9. Hooghe, L., Marks, G.: Cleavage theory meets europe’s crises: Lipset, rokkan, and the transnational cleavage. Journal of European public policy 25(1), 109–135 (2018) Bartolini and Mair [2007] Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  10. Bartolini, S., Mair, P.: Identity, Competition and Electoral Availability: the Stabilisation of European Electorates 1885-1985. ECPR Press, ??? (2007) Goldberg [2020] Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  11. Goldberg, A.C.: The evolution of cleavage voting in four western countries: Structural, behavioural or political dealignment? European Journal of Political Research 59(1), 68–90 (2020) Guerra et al. [2013] Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  12. Guerra, P.C., Meira Jr, W., Cardie, C., Kleinberg, R.: A measure of polarization on social media networks based on community boundaries. In: Seventh International AAAI Conference on Weblogs and Social Media (2013) Keuchenius et al. [2021] Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  13. Keuchenius, A., Törnberg, P., Uitermark, J.: Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a dutch cultural controversy on twitter. PloS one 16(8), 0256696 (2021) Barberá et al. [2015] Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  14. Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A., Bonneau, R.: Tweeting from left to right: Is online political communication more than an echo chamber? Psychological science 26(10), 1531–1542 (2015) Heider [1958] Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  15. Heider, F.: The Psychology of Interpersonal Relations. John Wiley & Sons Inc, Hoboken (1958). https://doi.org/10.1037/10628-000 Cartwright and Harary [1956] Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  16. Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological review 63(5), 277 (1956) Leskovec et al. [2010] Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  17. Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370 (2010) Estrada and Benzi [2014] Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  18. Estrada, E., Benzi, M.: Walk-based measure of balance in signed networks: Detecting lack of balance in social networks. Physical Review E 90(4), 042802 (2014) Aref and Wilson [2018] Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  19. Aref, S., Wilson, M.C.: Measuring partial balance in signed networks. Journal of Complex Networks 6(4), 566–595 (2018) Aref et al. [2020] Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  20. Aref, S., Dinh, L., Rezapour, R., Diesner, J.: Multilevel structural evaluation of signed directed social networks based on balance theory. Scientific reports 10(1), 1–12 (2020) Andres et al. [2022] Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  21. Andres, G., Casiraghi, G., Vaccario, G., Schweitzer, F.: Reconstructing signed relations from interaction data. arXiv preprint arXiv:2209.03219 (2022) Garcia and Tanase [2013] Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  22. Garcia, D., Tanase, D.: Measuring cultural dynamics through the eurovision song contest. Advances in Complex Systems 16(08), 1350037 (2013) Neal [2014] Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  23. Neal, Z.: The backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. Social Networks 39, 84–97 (2014) Tufekci [2014] Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  24. Tufekci, Z.: Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 505–514 (2014) Doreian and Mrvar [2015] Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  25. Doreian, P., Mrvar, A.: Structural balance and signed international relations. Journal of Social Structure 16(1), 1–49 (2015) Maoz et al. [2007] Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  26. Maoz, Z., Terris, L.G., Kuperman, R.D., Talmud, I.: What is the enemy of my enemy? causes and consequences of imbalanced international relations, 1816–2001. The Journal of Politics 69(1), 100–115 (2007) Diaz-Diaz et al. [2023] Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  27. Diaz-Diaz, F., Bartesaghi, P., Estrada, E.: Network theory meets history. local balance in global international relations. arXiv preprint arXiv:2303.03774 (2023) Estrada [2019] Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  28. Estrada, E.: Rethinking structural balance in signed social networks. Discrete Applied Mathematics 268, 70–90 (2019) Aref and Neal [2021] Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  29. Aref, S., Neal, Z.P.: Identifying hidden coalitions in the us house of representatives by optimally partitioning signed networks based on generalized balance. Scientific reports 11(1), 1–9 (2021) Guha et al. [2004] Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  30. Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412 (2004) Kunegis et al. [2009] Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  31. Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750 (2009) West et al. [2014] West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  32. West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. Transactions of the Association for Computational Linguistics 2, 297–310 (2014) Maniu et al. [2011] Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  33. Maniu, S., Cautis, B., Abdessalem, T.: Building a signed network from interactions in Wikipedia. In: Databases and Social Networks on - DBSocial ’11, pp. 19–24. ACM Press, Athens, Greece (2011). https://doi.org/10.1145/1996413.1996417 Pougué-Biyong et al. [2021] Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  34. Pougué-Biyong, J., Semenova, V., Matton, A., Han, R., Kim, A., Lambiotte, R., Farmer, D.: Debagreement: A comment-reply dataset for (dis) agreement detection in online debates. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) (2021) Pougué-Biyong et al. [2022] Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  35. Pougué-Biyong, J., Gupta, A., Haghighi, A., El-Kishky, A.: Learning stance embeddings from signed social graphs. arXiv preprint arXiv:2201.11675 (2022) Pröllochs [2022] Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  36. Pröllochs, N.: Community-based fact-checking on twitter’s birdwatch platform. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 16, pp. 794–805 (2022) Saeed et al. [2022] Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  37. Saeed, M., Traub, N., Nicolas, M., Demartini, G., Papotti, P.: Crowdsourced fact-checking at twitter: How does the crowd compare with experts? In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pp. 1736–1746 (2022) Drolsbach and Pröllochs [2023] Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  38. Drolsbach, C.P., Pröllochs, N.: Believability and harmfulness shape the virality of misleading social media posts. In: Proceedings of the ACM Web Conference 2023, pp. 4172–4177 (2023) Wojcik et al. [2022] Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  39. Wojcik, S., Hilgard, S., Judd, N., Mocanu, D., Ragain, S., Hunzaker, M., Coleman, K., Baxter, J.: Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation. arXiv preprint arXiv:2210.15723 (2022) Drolsbach and Pröllochs [2022] Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  40. Drolsbach, C., Pröllochs, N.: Diffusion of community fact-checked misinformation on twitter. arXiv preprint arXiv:2205.13673 (2022) Allen et al. [2022] Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  41. Allen, J., Martel, C., Rand, D.G.: Birds of a feather don’t fact-check each other: Partisanship and the evaluation of news in twitter’s birdwatch crowdsourced fact-checking program. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pp. 1–19 (2022) Niederkrotenthaler et al. [2022] Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  42. Niederkrotenthaler, T., Laido, Z., Kirchner, S., Braun, M., Metzler, H., Waldhör, T., Strauss, M., Garcia, D., Till, B.: Mental health over nine months during the sars-cov2 pandemic: Representative cross-sectional survey in twelve waves between april and december 2020 in austria. Journal of affective disorders 296, 49–58 (2022) Aref et al. [2020] Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  43. Aref, S., Mason, A.J., Wilson, M.C.: A modeling and computational study of the frustration index in signed networks. Networks 75(1), 95–110 (2020) Doreian and Mrvar [2009] Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  44. Doreian, P., Mrvar, A.: Partitioning signed social networks. Social Networks 31(1), 1–11 (2009) Schoch [2020] Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  45. Schoch, D.: Signnet: An R Package to Analyze Signed Networks. (2020). https://github.com/schochastics/signnet Davis [1967] Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  46. Davis, J.A.: Clustering and structural balance in graphs. Human relations 20(2), 181–187 (1967) Vijaymeena and Kavitha [2016] Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  47. Vijaymeena, M., Kavitha, K.: A survey on similarity measures in text mining. Machine Learning and Applications: An International Journal 3(2), 19–28 (2016) Gallagher et al. [2021] Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  48. Gallagher, R.J., Frank, M.R., Mitchell, L., Schwartz, A.J., Reagan, A.J., Danforth, C.M., Dodds, P.S.: Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts. EPJ Data Science 10(1), 4 (2021) Wikipedia [2023] Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  49. Wikipedia: Querfront — Wikipedia, die freie Enzyklopädie. [Online; Stand 12. September 2023] (2023). https://de.wikipedia.org/w/index.php?title=Querfront&oldid=236477099 [51] 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  50. 2015 European migrant crisis. Page Version ID: 1159102024 (2023). https://en.wikipedia.org/w/index.php?title=2015_European_migrant_crisis&oldid=1159102024 Accessed 2023-06-14 [52] 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  51. 2015–16 New Year’s Eve sexual assaults in Germany. Page Version ID: 1159999875 (2023). https://en.wikipedia.org/w/index.php?title=2015%E2%80%9316_New_Year%27s_Eve_sexual_assaults_in_Germany&oldid=1159999875 Accessed 2023-06-14 Garcia et al. [2015] Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  52. Garcia, D., Abisheva, A., Schweighofer, S., Serdült, U., Schweitzer, F.: Ideological and temporal components of network polarization in online political participatory media. Policy & internet 7(1), 46–79 (2015) Baldassarri and Gelman [2008] Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008) Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
  53. Baldassarri, D., Gelman, A.: Partisans without constraint: Political polarization and trends in american public opinion. American Journal of Sociology 114(2), 408–446 (2008)
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