Prestige bias drives the viral spread of content reposted by influencers in online communities

Abstract: Cultural evolution theory suggests that prestige bias - whereby individuals preferentially learn from prestigious figures - has played a key role in human ecological success. However, its impact within online environments remains unclear, particularly with respect to whether reposts by prestigious individuals amplify diffusion more effectively than reposts by noninfluential users. We analyzed over 55 million posts and 520 million reposts on Twitter (currently X) to examine whether users with high influence scores (hg indices) more effectively amplified the reach of others' content. Our findings indicate that posts shared by influencers are more likely to be further shared than those shared by non-influencers. This effect persisted over time, especially in viral posts. Moreover, a small group of highly influential users accounted for approximately half of the information flow within repost cascades. These findings demonstrate a prestige bias in information diffusion within the digital society, suggesting that cognitive biases shape content spread through reposting.

• The paper reveals that a small group of highly influential users drives about half of the content spread through their repost cascades.
• The paper demonstrates that prestige bias significantly elevates reposting power, with high hg-index users achieving much higher cascading repost probabilities.
• The paper introduces innovative frameworks like repost cascades and cascading repost probability, offering new insights for influencer marketing and misinformation management.

Analysis of Influencers' Reposts and Viral Diffusion: Prestige Bias in Online Communities

This study explores the role of influencers in information diffusion on social media platforms, with a particular focus on Twitter (currently known as X). It investigates the concept of prestige bias in online communities by examining how reposts by influencers impact the spread and virality of information. The authors employ a dataset comprising over 55 million posts and 520 million reposts to scrutinize whether a user's influence affects their ability to amplify external content through reposting activities.

Key Findings

The research introduces several innovative concepts, such as the repost cascade, secondary spread, and cascading repost probability (CRP), to analyze how information flows through online networks. The insights derived from these analyses illustrate that influencers, categorized as users with high hg-index scores, play a significant role in spreading content beyond their original creations.

1. Influence of Influencers on Information Diffusion: The study finds that a small group of highly influential users accounts for approximately half of the information flow in repost cascades. These influencers show enhanced capabilities for both primary and secondary spread, with significantly higher CRP, particularly for popular posts (≥ 1000 reposts).
2. Prestige Bias in Action: The results demonstrate a clear prestige bias in information diffusion. Influencers consistently achieve higher CRP scores over time, reinforcing their status and amplifying the subsequent diffusion of reposted content. This cognitive bias suggests a tendency for users to prefer and further disseminate information shared by socially prestigious individuals.
3. Qualitative Impact of Influencers: The analysis sheds light on the disproportionate impact of influencers in spreading popular content. While very high influence users comprise only 1% of the user population, they account for a substantial share of views and reposts, demonstrating their pivotal role in both the early and viral stages of information dissemination.
4. Impact on Viral Diffusion Dynamics: The study identifies that influencers not only broadcast information to their extensive follower networks but also act as catalysts for viral diffusion. Influencer-shared content exhibits higher structural virality and extended cascade depths, illustrating their effectiveness in encouraging further reposts from their audience.

Implications and Future Research

The implications of these findings are multifaceted, affecting theoretical understanding and practical applications. The demonstration of prestige bias in online communities highlights the influential power of social status in digital communication and the potential for influencers to shape online discourse substantially. These insights are particularly relevant for designing more effective influencer marketing strategies and developing interventions to manage misinformation spread.

Future research could delve further into the nuanced dynamics of information spread shaped by content characteristics, exploring how prestige bias interacts with content quality. Investigating the potential role of influencers in correcting or exacerbating misinformation may also be fruitful, assisting in crafting informed policies that leverage their capabilities while minimizing negative consequences.

In conclusion, this study provides compelling evidence supporting the prevalence of prestige bias in online information diffusion. It underscores the significant role that influencers play in amplifying content reach and shaping information dynamics in digital spheres. The introduction of new analytical frameworks, such as repost cascades and CRP, enriches the existing literature by offering refined tools for studying social media diffusion patterns.