Volltext-Downloads (blau) und Frontdoor-Views (grau)

Nonlinear agent-based dynamics: which metric mitigates polarization?

  • This article provides a stochastic agent-based model to exhibit the role of aggregation metrics in order to mitigate polarization in a complex society. Our sociophysics model is based on interacting and nonlinear Brownian agents, which allow us to study the emergence of collective opinions. The opinion of an agent, x i (t) is a continuous positive value in an interval [0, 1]. We find (i) most agent-metrics display similar outcomes. (ii) The middle-metric and noisy-metric obtain new opinion dynamics either towards assimilation or fragmentation. (iii) We show that a developed 2-stage metric provide new insights about convergence and equilibria. In summary, our simulation demonstrates the power of institutions, which affect the emergence of collective behavior. Consequently, opinion formation in a decentralized complex society is reliant to the individual information processing and rules of collective behavior.

Export metadata

Additional Services

Share in Twitter Search Google Scholar


Author of HS ReutlingenHerzog, Bodo
Erschienen in:Journal of computational and nonlinear dynamics
Place of publication:New York, NY
Document Type:Journal article
Publication year:2023
Tag:agent-based modelling; bounded confidence model; nonlinear dynamical system; opinion dynamics; sociophyics
Page Number:6
Article Number:034501
DDC classes:004 Informatik
Open access?:Nein