Cascade-driven opinion dynamics on social networks

TL;DR

This paper introduces the FJC model, integrating information cascades with opinion dynamics on social networks, revealing how cascades amplify influence of central leaders and affect opinion evolution.

Contribution

It presents the first model combining information cascades with Friedkin-Johnsen opinion dynamics, validated on real social data, highlighting their impact on opinion formation.

Findings

Cascades amplify influence of central opinion leaders.

Cascades make opinions more resistant to dissent.

Disruption of offline opinion dynamics in online settings.

Abstract

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.