Cascade-driven opinion dynamics on social networks
This research addresses the impact of online social networks on public discourse, offering insights into how information flow shapes opinions, though it appears incremental by combining existing models.
The paper tackles the problem of how information cascades on social networks influence opinion dynamics by proposing the FJC model, which integrates cascades with the Friedkin-Johnsen model, and finds that cascades amplify the influence of central opinion leaders, making them resistant to dissent.
Online social networks (OSNs) have transformed the way individuals fulfill their social needs and consume information. As OSNs become increasingly prominent sources for news dissemination, individuals often encounter content that influences their opinions through both direct interactions and broader network dynamics. In this paper, we propose the Friedkin-Johnsen on Cascade (FJC) model, which is, to the best of our knowledge, is the first attempt to integrate information cascades and opinion dynamics, specifically using the very popular Friedkin-Johnsen model. Our model, validated over real social cascades, highlights how the convergence of socialization and sharing news on these platforms can disrupt opinion evolution dynamics typically observed in offline settings. Our findings demonstrate that these cascades can amplify the influence of central opinion leaders, making them more resistant to divergent viewpoints, even when challenged by a critical mass of dissenting opinions. This research underscores the importance of understanding the interplay between social dynamics and information flow in shaping public discourse in the digital age.