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Opinion dynamics in social networks: From models to data

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arxiv 2201.01322 v4 pith:2EHH5LHO submitted 2022-01-04 physics.soc-ph cs.CYcs.SInlin.AO

classification physics.soc-phcs.CYcs.SInlin.AO
keywords datamodelsopinionsocialchangedynamicsactionagreement
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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.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Social Contagion in COVID-19 Discussions within the Belgian Reddit Community: A Statistical and Modeling Study

    cs.SI 2025-05 conditional novelty 6.0 of 10

    In r/Belgium, COVID-19 topics were seeded by external events, not by prior posts, but comment sentiment was contagious, and a two-layer bounded confidence model best captured that asymmetry.

  2. Patterns, Models, and Challenges in Online Social Media: A Survey

    cs.SI 2025-07 conditional novelty 1.0 of 10

    A survey of online social media research argues the field is fragmented and must move toward comparative, data-validated models.

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