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Opinion dynamics: Statistical physics and beyond

Michele Starnini, Fabian Baumann, Tobias Galla, David Garcia, Gerardo Iñiguez, Márton Karsai, Jan Lorenz, and Katarzyna Sznajd-Weron

Michele Starnini

Fabian Baumann

Tobias Galla

  • Institute for Cross-Disciplinary Physics and Complex Systems (IFISC UIB-CSIC), Edifici Instituts Universitaris de Recerca, Campus Universitat de les Illes Balears, E-07122 Palma, Spain

David Garcia

Gerardo Iñiguez

Márton Karsai

Jan Lorenz

Katarzyna Sznajd-Weron

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Rev. Mod. Phys. 98, 035004 – Published 10 September, 2026

DOI: https://doi.org/10.1103/j1zg-ddqv

Abstract

Opinion dynamics, the study of how individual beliefs and collective public opinion evolve, is a fertile domain for applying the framework of statistical physics to complex social phenomena. Like physical systems, societies exhibit macroscopic regularities arising from numerous localized interactions, leading to an outcome such as consensus or fragmentation. Opinion dynamics has grown from a fringe interest to an active field of physics, attracting interdisciplinary methods from computer science, economics, and sociology. This review covers the ongoing rapid progress in the field, driven by an unprecedented surge in available large-scale behavioral data, bridging the inherently interdisciplinary literature. The review begins with essential concepts and definitions, encompassing the nature of opinions and their microscopic and macroscopic dynamics. This foundation leads to an overview of empirical research, from lab experiments to large-scale data analysis, which informs and validates models of opinion dynamics. Models are then categorized by the macroscopic phenomena they describe (for example, consensus, polarization, and echo chambers) and the microscopic mechanisms of opinion change they encode (for example, homophily and assimilation). The review covers common analytical and computational tools for studying these models, such as stochastic processes, exact and approximate treatments, simulation techniques, and optimization methods. Finally, the review explores emerging frontiers, including the ongoing effort to establish a closer connection between empirical data and models and the recent developments in building artificial intelligence agents as test beds for novel social phenomena. By systematizing terminology across disciplines and emphasizing analogies with traditional physics, the review highlights connections between theoretical models, concepts in social psychology, and observable societal phenomena. This review aims to consolidate current knowledge, provide a robust theoretical foundation, and shape future research directions in opinion dynamics.

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Rev. Mod. Phys. 98, 035004– Published 10 September, 2026
  • Received 4 July 2024
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