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Discord in the voter model for complex networks

Vendeville, Antoine; Zhou, Shi; Guedj, Benjamin; (2024) Discord in the voter model for complex networks. Physical Review E , 109 (2) , Article 024312. 10.1103/physreve.109.024312. Green open access

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Abstract

Online social networks have become primary means of communication. As they often exhibit undesirable effects such as hostility, polarization, or echo chambers, it is crucial to develop analytical tools that help us better understand them. In this paper we are interested in the evolution of discord in social networks. Formally, we introduce a method to calculate the probability of discord between any two agents in the multistate voter model with and without zealots. Our work applies to any directed, weighted graph with any finite number of possible opinions, allows for various update rates across agents, and does not imply any approximation. Under certain topological conditions, the opinions are independent and the joint distribution can be decoupled. Otherwise, the evolution of discord probabilities is described by a linear system of ordinary differential equations. We prove the existence of a unique equilibrium solution, which can be computed via an iterative algorithm. The classical definition of active links density is generalized to take into account long-range, weighted interactions. We illustrate our findings on real-life and synthetic networks. In particular, we investigate the impact of clustering on discord and uncover a rich landscape of varied behaviors in polarized networks. This sheds lights on the evolution of discord between, and within, antagonistic communities.

Type: Article
Title: Discord in the voter model for complex networks
Open access status: An open access version is available from UCL Discovery
DOI: 10.1103/physreve.109.024312
Publisher version: http://dx.doi.org/10.1103/physreve.109.024312
Language: English
Additional information: Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license, https://creativecommons.org/licenses/by/4.0/. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10188070
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