Opinion dynamics: Statistical physics and beyond

TL;DR

This review synthesizes recent advances in opinion dynamics, applying statistical physics concepts to understand how individual beliefs evolve into collective social phenomena like consensus or polarization.

Contribution

It provides a comprehensive overview of models, empirical research, and analytical tools in opinion dynamics, bridging interdisciplinary methods and highlighting future directions.

Findings

Empirical data supports models of consensus and polarization.

Analytical tools include stochastic processes and simulations.

Emerging frontiers involve AI agents and data-model integration.

Abstract

Opinion dynamics, the study of how individual beliefs and collective public opinion evolve, is a fertile domain for applying statistical physics to complex social phenomena. Like physical systems, societies exhibit macroscopic regularities from localized interactions, leading to outcomes such as consensus or fragmentation. This field has grown significantly, attracting interdisciplinary methods and driven by a surge in large-scale behavioral data. This review covers its rapid progress, bridging the literature dispersion. We begin with essential concepts and definitions, encompassing the nature of opinions, 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. We then present individual-based models, categorized by their macroscopic phenomena (e.g., consensus, polarization, echo chambers) and microscopic mechanisms (e.g., homophily, assimilation). Furthermore, the review covers common analytical and computational tools, including stochastic processes, treatments, simulations, and optimization. Finally, we explore emerging frontiers, such as connecting empirical data to models and using AI agents as testbeds for novel social phenomena. By systematizing terminology and emphasizing analogies with traditional physics, this review aims to consolidate knowledge, provide a robust theoretical foundation, and shape future research in opinion dynamics.