Opinion dynamics on biased dynamical networks: beyond rare opinion updating

Fuente: arXiv
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Autores principales: Wang, Xunlong, Wu, Bin
Formato: Preprint
Publicado: 2024
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author Wang, Xunlong
Wu, Bin
author_facet Wang, Xunlong
Wu, Bin
contents Opinion dynamics is of paramount importance as it provides insights into the complex dynamics of opinion propagation and social relationship adjustment. It is assumed in most of the previous works that social relationships evolve much faster than opinions. This is not always true in reality. We propose an analytical approximation to study this issue for arbitrary time scales between opinion adjustment and network evolution. To this end, the coefficient of determination in statistics is introduced and a one-dimensional stable manifold is analytically found, i.e., the most likely trajectory. With the aid of the stable manifold, we further obtain the fate of opinions and the consensus time, i.e., fixation probability and fixation time. We find that for in-group bias, the more likely individuals are to adopt the popular opinion, the less likely the majority opinion takes over the population, i.e., conformity inhibits the domination of popular opinions. This counter-intuitive result can be interpreted from a game perspective, in which in-group bias refers to a coordination game and rewiring probability refers to a rescaling of the selection intensity. Our work proposes an efficient approximation method to foster the understanding of opinion dynamics in dynamical networks.
format Preprint
id arxiv_https___arxiv_org_abs_2404_02913
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Opinion dynamics on biased dynamical networks: beyond rare opinion updating
Wang, Xunlong
Wu, Bin
Physics and Society
Populations and Evolution
Opinion dynamics is of paramount importance as it provides insights into the complex dynamics of opinion propagation and social relationship adjustment. It is assumed in most of the previous works that social relationships evolve much faster than opinions. This is not always true in reality. We propose an analytical approximation to study this issue for arbitrary time scales between opinion adjustment and network evolution. To this end, the coefficient of determination in statistics is introduced and a one-dimensional stable manifold is analytically found, i.e., the most likely trajectory. With the aid of the stable manifold, we further obtain the fate of opinions and the consensus time, i.e., fixation probability and fixation time. We find that for in-group bias, the more likely individuals are to adopt the popular opinion, the less likely the majority opinion takes over the population, i.e., conformity inhibits the domination of popular opinions. This counter-intuitive result can be interpreted from a game perspective, in which in-group bias refers to a coordination game and rewiring probability refers to a rescaling of the selection intensity. Our work proposes an efficient approximation method to foster the understanding of opinion dynamics in dynamical networks.
title Opinion dynamics on biased dynamical networks: beyond rare opinion updating
topic Physics and Society
Populations and Evolution
url https://arxiv.org/abs/2404.02913