# Opinion dynamics in social networks: From models to data

arXiv: https://arxiv.org/abs/2201.01322 · HTML: https://mlsanity.com/paper/2201.01322/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Jan 2022.

## Built on by (most cited first, 6 of 6)

- [How Social is It? A Benchmark for LLMs' Capabilities in Multi-user Multi-turn Social Agent Tasks](https://mlsanity.com/paper/2505.04628/) (2025)
- [Variational Inference of Parameters in Opinion Dynamics Models](https://mlsanity.com/paper/2403.05358/) (2024)
- [Exploration of the generative capabilities of Boltzmann machines applied to social systems under the majority rule](https://mlsanity.com/paper/2607.23349/) (2026)
- [Questions of science: chatting with ChatGPT about complex systems](https://mlsanity.com/paper/2303.16870/) (2023)
- [Phase Transitions of Civil Unrest across Countries and Time](https://mlsanity.com/paper/2306.08698/) (2023)
- [LLM Agents Make Collective Belief Dynamics Programmable: Challenges and Research Directions](https://mlsanity.com/paper/2605.19915/) (2026)

## Abstract (arXiv)

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.