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Updated: Oct 2, 2025

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Opinion Evolution in Divided Community.

Tomasz Weron¹, Janusz Szwabiński¹

¹Hugo Steinhaus Center, Faculty of Pure and Applied Mathematics, Wrocław University of Science and Technology, 50-370 Wrocław, Poland.

Entropy (Basel, Switzerland)

|February 25, 2022

Summary

This summary is machine-generated.

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Social polarization occurs when communities divide into opposing groups. This study shows that negative social ties are crucial for polarization, and independent actions can surprisingly aid this process unless too frequent.

Area of Science:

Computational social science
Sociophysics
Opinion dynamics

Background:

Modern societies face increasing divisions and polarization.
Understanding the mechanisms driving social polarization is crucial.

Purpose of the Study:

To model social polarization using an agent-based approach.
To investigate how mutual animosities and independent actions influence radicalization and polarization.

Main Methods:

Developed an agent-based model with binary opinions and a double-clique topology.
Incorporated positive (conformity) and negative (opposition) ties.
Utilized Monte-Carlo simulations and a mean-field approach.

Main Results:

Keywords:

Monte-Carlo simulation agent-based model opinion dynamics social polarization

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Last Updated: Oct 2, 2025

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

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Identified a critical threshold of negative relations necessary for polarization.

Found that independent actions can unexpectedly promote polarization.

Observed that high frequencies of independent actions lead to system disorder.

Conclusions:

Social polarization is contingent on a sufficient level of negative intergroup relations.
Individual independence can paradoxically reinforce societal divisions, up to a certain frequency limit.