@inproceedings{e6b66783f24e4c5ab4d6aeb56a063a02,
title = "Identity Drives Polarization: Advancing the Hegselmann-Krause Model by Identity Groups",
abstract = "In this article we describe an Agent-Based Model that extends the Hegselmann-Krause model of opinion dynamics to study the role of social identity in opinion polarization. In our model, an agent{\textquoteright}s social identity is a function of two things—the agent{\textquoteright}s opinion in relation to those of the other agents, and the observer{\textquoteright}s sensitivity to the tightness of clustering. We implement this by first selecting a subset of the agent population that are deemed to have close neighbors, and then using Louvain community detection to find identity groups. At every time step, agents only consider the opinions of other agents within their identity group that also fall within their Hegselmann-Krause opinion boundary, ε. We show that our dynamic implementation of social identity systematically modulates the relationship between average ε and polarization.",
keywords = "Bounded confidence model, Dynamic identity, Polarization",
author = "Franti{\v s}ek Kalvas and Ashwin Ramaswamy and Slater, {Michael D.}",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 17th annual conference of European Social Simulation Association, ESSA 2022 ; Conference date: 12-09-2022 Through 16-09-2022",
year = "2023",
doi = "10.1007/978-3-031-34920-1_20",
language = "English",
isbn = "9783031349195",
series = "Springer Proceedings in Complexity",
publisher = "Springer Science and Business Media B.V.",
pages = "249--262",
editor = "Flaminio Squazzoni",
booktitle = "Advances in Social Simulation - Proceedings of the 17th Social Simulation Conference, European Social Simulation Association",
}