ArticleJournal of the Royal Society, Interface2021
Integrating social and cognitive aspects of belief dynamics: towards a unifying framework.
Article in Journal of the Royal Society, Interface, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
28 citing papers in PubMed.
- Integrating behavioural experimental findings into dynamical models to inform social change interventions.Nature human behaviour · 2026Article
- Cultural tightness and social cohesion under coevolving beliefs, behaviors, and preferences.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- The desire to avoid cognitive dissonance drives community formation in a social network model.Scientific reports · 2025Article
- Why more social interactions lead to more polarization in societies.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- A semantic embedding space based on large language models for modelling human beliefs.Nature human behaviour · 2025Article
- Empowering safer socially sensitive autonomous vehicles using human-plausible cognitive encoding.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Collective effect of self-learning and social learning on language dynamics: a naming game approach in social networks.Journal of the Royal Society, Interface · 2024Article
- Emergence of simple and complex contagion dynamics from weighted belief networks.Science advances · 2024Article
- Noise and opinion dynamics: how ambiguity promotes pro-majority consensus in the presence of confirmation bias.Royal Society open science · 2024Article
- Modelling social norms: an integration of the norm-utility approach with beliefs dynamics.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Review
- Implicit racial biases are lower in more populous more diverse and less segregated US cities.Nature communications · 2024Article
- Escape from fraught states in a coordination game.Royal Society open science · 2024Article
- Co-evolution of behaviour and beliefs in social dilemmas: estimating material, social, cognitive and cultural determinants.Evolutionary human sciences · 2024Article
- Social identity bias and communication network clustering interact to shape patterns of opinion dynamics.Journal of the Royal Society, Interface · 2023Article
- Humans strategically avoid connecting to others who agree and avert the emergence of network polarization in a coordination task.Scientific reports · 2023Article
- Pathways to the persistence of drug use despite its adverse consequences.Molecular psychiatry · 2023Review
- Voter-like Dynamics with Conflicting Preferences on Modular Networks.Entropy (Basel, Switzerland) · 2023Article
- Assumed shared belief about conspiracy theories in social networks protects paranoid individuals against distress.Scientific reports · 2023Article
- Beyond collective intelligence: Collective adaptation.Journal of the Royal Society, Interface · 2023Review
- A 10-year prospectus for mathematical epidemiology.Frontiers in psychology · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Belief change and spread have been studied in many disciplines-from psychology, sociology, economics and philosophy, to biology, computer science and statistical physics-but we still do not have a firm grasp on why some beliefs change more easily and spread faster than others. To fully capture the complex social-cognitive system that gives rise to belief dynamics, we first review insights about structural components and processes of belief dynamics studied within different disciplines. We then outline a unifying quantitative framework that enables theoretical and empirical comparisons of different belief dynamic models. This framework uses a statistical physics formalism, grounded in cognitive and social theory, as well as empirical observations. We show how this framework can be used to integrate extant knowledge and develop a more comprehensive understanding of belief dynamics.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.