Cascade-driven opinion dynamics on social networks

Fuente: arXiv
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Main Authors: Biondi, Elisabetta, Boldrini, Chiara, Passarella, Andrea, Conti, Marco
Format: Preprint
Published: 2025
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author Biondi, Elisabetta
Boldrini, Chiara
Passarella, Andrea
Conti, Marco
author_facet Biondi, Elisabetta
Boldrini, Chiara
Passarella, Andrea
Conti, Marco
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2506_16302
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Cascade-driven opinion dynamics on social networks
Biondi, Elisabetta
Boldrini, Chiara
Passarella, Andrea
Conti, Marco
Social and Information Networks
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.
title Cascade-driven opinion dynamics on social networks
topic Social and Information Networks
url https://arxiv.org/abs/2506.16302