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A Multi-agent Model for Polarization Under Confirmation Bias in Social Networks

  • Mário S. Alvim
  • , Bernardo Amorim
  • , Sophia Knight
  • , Santiago Quintero
  • , Frank Valencia

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Résumé

We describe a model for polarization in multi-agent systems based on Esteban and Ray’s standard measure of polarization from economics. Agents evolve by updating their beliefs (opinions) based on an underlying influence graph, as in the standard DeGroot model for social learning, but under a confirmation bias; i.e., a discounting of opinions of agents with dissimilar views. We show that even under this bias polarization eventually vanishes (converges to zero) if the influence graph is strongly-connected. If the influence graph is a regular symmetric circulation, we determine the unique belief value to which all agents converge. Our more insightful result establishes that, under some natural assumptions, if polarization does not eventually vanish then either there is a disconnected subgroup of agents, or some agent influences others more than she is influenced. We also show that polarization does not necessarily vanish in weakly-connected graphs under confirmation bias. We illustrate our model with a series of case studies and simulations, and show how it relates to the classic DeGroot model for social learning.

langue originaleAnglais
titreFormal Techniques for Distributed Objects, Components, and Systems - 41st IFIP WG 6.1 International Conference, FORTE 2021, Held as Part of the 16th International Federated Conference on Distributed Computing Techniques, DisCoTec 2021, Proceedings
rédacteurs en chefKirstin Peters, Tim A. Willemse
EditeurSpringer Science and Business Media Deutschland GmbH
Pages22-41
Nombre de pages20
ISBN (imprimé)9783030780883
Les DOIs
étatPublié - 1 janv. 2021
Evénement41st IFIP WG 6.1 International Conference on Formal Techniques for Distributed Objects, Components, and Systems, FORTE 2021 held as part of 16th International Federated Conference on Distributed Computing Techniques, DisCoTec 2021 - Virtual, Online
Durée: 14 juin 202118 juin 2021

Série de publications

NomLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12719 LNCS
ISSN (imprimé)0302-9743
ISSN (Electronique)1611-3349

Une conférence

Une conférence41st IFIP WG 6.1 International Conference on Formal Techniques for Distributed Objects, Components, and Systems, FORTE 2021 held as part of 16th International Federated Conference on Distributed Computing Techniques, DisCoTec 2021
La villeVirtual, Online
période14/06/2118/06/21

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