Li, X, Mobilia, M orcid.org/0000-0002-1424-567X, Rucklidge, AM orcid.org/0000-0003-2985-0976 et al. (1 more author) (Cover date: January 2022) Effects of homophily and heterophily on preferred-degree networks: mean-field analysis and overwhelming transition. Journal of Statistical Mechanics: Theory and Experiment, 2022 (1). 013402. ISSN 1742-5468
Abstract
We investigate the long-time properties of a dynamic, out-of-equilibrium network of individuals holding one of two opinions in a population consisting of two communities of different sizes. Here, while the agents' opinions are fixed, they have a preferred degree which leads them to endlessly create and delete links. Our evolving network is shaped by homophily/heterophily, a form of social interaction by which individuals tend to establish links with others having similar/dissimilar opinions. Using Monte Carlo simulations and a detailed mean-field analysis, we investigate how the sizes of the communities and the degree of homophily/heterophily affect the network structure. In particular, we show that when the network is subject to enough heterophily, an 'overwhelming transition' occurs: individuals of the smaller community are overwhelmed by links from the larger group, and their mean degree greatly exceeds the preferred degree. This and related phenomena are characterized by the network's total and joint degree distributions, as well as the fraction of links across both communities and that of agents having fewer edges than the preferred degree. We use our mean-field theory to discuss the network's polarization when the group sizes and level of homophily vary.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 IOP Publishing Ltd and SISSA Medialab srl. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | network dynamics, agent-based models, stochastic processes |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Applied Mathematics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 30 Nov 2021 15:37 |
Last Modified: | 14 Mar 2023 07:09 |
Status: | Published |
Publisher: | IOP Publishing |
Identification Number: | 10.1088/1742-5468/ac410f |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:180982 |