The generation and regulation of public opinion on multiplex social networks

Abstract: The dissemination of information and the development of public opinion are essential elements of most social media platforms and are often described as distinct, man-made occurrences. However, what is often disregarded is the interdependence between these two phenomena. Information dissemination serves as the foundation for the formation of public opinion, while public opinion, in turn, drives the spread of information. In our study, we model the co-evolutionary relationship between information and public opinion on heterogeneous multiplex networks. This model takes into account a minority of individuals with steadfast opinions and a majority of individuals with fluctuating views. Our findings reveal the equilibrium state of public opinion in this model and a linear relationship between mainstream public opinion and extreme individuals. Additionally, we propose a strategy for regulating public opinion by adjusting the positions of extreme groups, which could serve as a basis for implementing health policies influenced by public opinion.

• The paper introduces a duplex network model that couples information diffusion and opinion formation to reveal underlying public opinion dynamics.
• It employs heat conduction and quenched mean-field techniques to quantify steady-state opinion distributions and the influence of network topology.
• Results show that hub nodes with extreme views significantly sway mainstream opinion, offering strategic pathways for effective public opinion regulation.

The Generation and Regulation of Public Opinion on Multiplex Social Networks

Introduction

The paper discusses a model addressing the intricate dynamics of information dissemination and public opinion formation on multiplex social networks. It explores the interdependencies between the dissemination of information and public opinion dynamics, emphasizing that they mutually reinforce each other. This interaction is modeled using a duplex network structure to better capture the complexities involved in these processes.

Information-Opinion Model

The authors introduce an information-opinion model situated on a duplex network. In this model, sets of nodes and edges represent individuals and their connections within two distinct layers: one for information dissemination and another for opinion formation. The adjacency matrices for these layers, denoted as $A^I$ and $A^O$, respectively, guide the flow of information and opinions. The dynamics account for individuals whose states change over time as they interact with their neighbors, including transitioning between "unknown" and "active" information states or between various opinion states ranging from extreme opposition to support.

Steady-State Distribution of Opinions

The authors employ heat conduction modeling and quenched mean-field techniques to derive the steady-state distribution of opinions. The approach involves quantifying the probabilities of individual nodes being informed and active, which eventually determines their influence in opinion dynamics. The interplay between opinion evolution and network topology leads to a bell-shaped distribution centered around mainstream opinion. Notably, the integration of extreme nodes, those with steadfast opinions, alters the steady-state distributions significantly.

Consistency and Correlations with Network Structure

The paper highlights the correlation between the topology of network structures and public opinion distributions. A topological correlation index is proposed to quantify how closely public opinions align with network structures. The results showed a positive correlation, meaning that nodes tend to have similar opinions to their connected peers, leading to clustered opinion groups within the network.

Mainstream Opinion and Node Influence

The authors establish a mathematical relationship between mainstream public opinion and the influence exerted by extreme individuals based on their network positions. They demonstrate that nodes with higher connectivity (hub nodes) have a disproportionate effect on swaying the mainstream opinion if they hold extreme views. This finding underscores the strategic importance of key nodes in opinion regulation efforts.

Public Opinion Regulation Strategy

The paper proposes a strategy for regulating public opinion by manipulating the positions of extreme opinion holders within the network. By adjusting the number and influence of extreme nodes, particularly those at hubs, the model suggests that mainstream opinion can be directed between extreme viewpoints. This method could be instrumental in crafting effective public health policies or other interventions influenced by public opinion.

Conclusion

This study advances the understanding of dynamic public opinion and information dissemination processes within multiplex networks. By grounding the model in both theoretical analysis and empirical data, it provides insights into effectively managing public opinion through strategic interventions. Future work can extend this framework to consider real-world data and refine public opinion regulation methodologies. Such developments hold significant implications for areas like public health policy where controlling the flow and impact of information is critical.