Diversity mitigates polarization and consensus in opinion dynamics

Fuente: arXiv
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Autori principali: Pradhan, Sidharth, Ujjwal, Sangeeta Rani
Natura: Preprint
Pubblicazione: 2025
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author Pradhan, Sidharth
Ujjwal, Sangeeta Rani
author_facet Pradhan, Sidharth
Ujjwal, Sangeeta Rani
contents We study the opinion dynamics in a population by considering a variant of Kuramoto model where the phase of an oscillator represents the opinion of an individual on a single topic. Two extreme phases separated by $π$ represent opposing views. Any other phase is considered as an intermediate opinion between the two extremes. The interaction (or attitude) between two individuals depends on the difference between their opinions and can be positive (attractive) or negative (repulsive) based on the defined thresholds. We investigate the opinion dynamics when these thresholds are varied. We observe explosive transition from a bipolarized state to a consensus state with the existence of scattered and tri-polarized states at low values of threshold parameter. The system exhibits multistability between various states in a sizeable parameter region. These transitions and multistability are studied in populations with different degrees of diversity represented by the width of conviction distribution. We found that a more homogeneous population has greater tendency to exhibit bipolarized, tri-polarized and clustered states while a diverse population helps mitigate polarization among individuals by reaching to a consensus sooner. Ott-Antonsen analysis is used to analyse the system's long term macroscopic behaviour and verify the numerical results. We also study the effects of neutral individuals that do not interact with others or do not change their attitude on opinion formation, nature of transitions and multistability. Furthermore, we apply our model to language data to study the assimilation of diverse languages in India and compare the results with those obtained from model equations.
format Preprint
id arxiv_https___arxiv_org_abs_2509_19860
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Diversity mitigates polarization and consensus in opinion dynamics
Pradhan, Sidharth
Ujjwal, Sangeeta Rani
Physics and Society
Adaptation and Self-Organizing Systems
We study the opinion dynamics in a population by considering a variant of Kuramoto model where the phase of an oscillator represents the opinion of an individual on a single topic. Two extreme phases separated by $π$ represent opposing views. Any other phase is considered as an intermediate opinion between the two extremes. The interaction (or attitude) between two individuals depends on the difference between their opinions and can be positive (attractive) or negative (repulsive) based on the defined thresholds. We investigate the opinion dynamics when these thresholds are varied. We observe explosive transition from a bipolarized state to a consensus state with the existence of scattered and tri-polarized states at low values of threshold parameter. The system exhibits multistability between various states in a sizeable parameter region. These transitions and multistability are studied in populations with different degrees of diversity represented by the width of conviction distribution. We found that a more homogeneous population has greater tendency to exhibit bipolarized, tri-polarized and clustered states while a diverse population helps mitigate polarization among individuals by reaching to a consensus sooner. Ott-Antonsen analysis is used to analyse the system's long term macroscopic behaviour and verify the numerical results. We also study the effects of neutral individuals that do not interact with others or do not change their attitude on opinion formation, nature of transitions and multistability. Furthermore, we apply our model to language data to study the assimilation of diverse languages in India and compare the results with those obtained from model equations.
title Diversity mitigates polarization and consensus in opinion dynamics
topic Physics and Society
Adaptation and Self-Organizing Systems
url https://arxiv.org/abs/2509.19860