https://doi.org/10.1140/epjb/s10051-024-00762-9
Regular Article – Statistical and Nonlinear Physics
Bounded confidence opinion dynamics with Asch-like social conformity in complex networks
1
Instituto de Física, Universidade Federal do Rio Grande do Sul, Av. Bento Gonçalves, 9500, 91509-900, Porto Alegre, RS, Brazil
2
TRM Labs, San Francisco, CA, USA
Received:
19
March
2024
Accepted:
29
July
2024
Published online:
2
September
2024
Computational models of peer interaction, with or without networks, have been applied to opinion dynamics to describe social phenomena. Here, we use the Deffuant–Weisbuch (DW) model of opinion dynamics, where a confidence parameter bounds individuals’ interactions, both in paradigmatic artificial networks and some social networks. The interaction of an individual with their immediate neighbors is incorporated into the model using Asch’s concept of social conformity. In general, conformity facilitates consensus in networks by reducing the time required to reach a state of equilibrium and by increasing the likelihood of a single opinion value prevailing throughout the network. In real networks, a higher probability of adherence () to the majority opinion increases the proportion of individuals in consensus within less tolerant networks (). Conformity leads to more nodes agreeing around the same average opinion in a shorter time.
Sebastián Gonçalves and Bruno Requião da Cunha contributed equally to this work.
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© The Author(s), under exclusive licence to EDP Sciences, SIF and Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.