Opinion dynamics in social networks: From models to data

TL;DR

This paper reviews models and data on opinion dynamics in social networks, aiming to understand how individual opinions evolve and lead to collective states like consensus or polarization, with implications for societal challenges.

Contribution

It synthesizes idealized models and empirical data on opinion dynamics, highlighting efforts to bridge the gap between theory and observation in social sciences.

Findings

Models explain how opinions evolve and polarize.

Empirical data validates some theoretical models.

Bridging models and data can inform societal challenge solutions.

Abstract

Opinions are an integral part of how we perceive the world and each other. They shape collective action, playing a role in democratic processes, the evolution of norms, and cultural change. For decades, researchers in the social and natural sciences have tried to describe how shifting individual perspectives and social exchange lead to archetypal states of public opinion like consensus and polarization. Here we review some of the many contributions to the field, focusing both on idealized models of opinion dynamics, and attempts at validating them with observational data and controlled sociological experiments. By further closing the gap between models and data, these efforts may help us understand how to face current challenges that require the agreement of large groups of people in complex scenarios, such as economic inequality, climate change, and the ongoing fracture of the sociopolitical landscape.