Abstract (may include machine translation)
Opinions are integral to 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.
| Original language | English |
|---|---|
| Title of host publication | Handbook of Computational Social Science |
| Editors | Taha Yasseri |
| Publisher | Edward Elgar Publishing Ltd. |
| Pages | 384-406 |
| Number of pages | 23 |
| ISBN (Electronic) | 9781802207309 |
| ISBN (Print) | 9781802207293 |
| DOIs | |
| State | Published - Dec 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 10 Reduced Inequalities
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SDG 13 Climate Action
Keywords
- Bounded Confidence Models
- Opinion Dynamics
- Polarization and Algorithmic Bias
- Social Networks
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