Modeling echo chambers and polarization dynamics in social networks
By Fabian Baumann, Philipp Lorenz-Spreen, Igor M. Sokolov, Michele Starnini. Physical Review Letters, 2019
373 citations recorded by the source corpus.
Echo chambers and opinion polarization recently quantified in several sociopolitical contexts and across different social media raise concerns on their potential impact on the spread of misinformation and on the openness of debates. Despite increasing efforts, the dynamics leading to the emergence of these phenomena remain unclear. We propose a model that introduces the dynamics of radicalization as a reinforcing mechanism driving the evolution to extreme opinions from moderate initial conditions. Inspired by empirical findings on social interaction dynamics, we consider agents characterized by heterogeneous activities and homophily. We show that the transition between a global consensus and emerging radicalized states is mostly governed by social influence and by the controversialness of the topic discussed. Compared with empirical data of polarized debates on Twitter, the model qualitatively reproduces the observed relation between users' engagement and opinions, as well as opinion segregation in the interaction network. Our findings shed light on the mechanisms that may lie at the core of the emergence of echo chambers and polarization in social media.
Subfields: Economics and Econometrics, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/1ad1c78329fc97906d15cb131d57df8a51a82c62
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In Statistical and Nonlinear Physics
Citations in the corpus
- S3: Social-network Simulation System with Large Language Model-Empowered Agents (2023, neutral): “Great efforts have been made to quantify real-world polarization [22, 12, 16] and simulate the polarization process using co-evolution model [31, 3, 4, 20].”
- The COVID-19 social media infodemic (2020, background): “ing during critical events. While R 0 is a good proxy for the engagement rate and a good predictor for epidemic-like information spreading, social contagion phenomena might be in general more complex [34, 35, 36]. For instance, in the case of Instagram, we observe an abrupt jump in the number of new”
- The echo chamber effect on social media (2021, background): “Some studies point out echo chambers as an emerging effect of human tendencies, such as selective exposure, contagion, and group polarization (13, 23, 29–31).”