ArticleScientific reports2020
A network-based microfoundation of Granovetter's threshold model for social tipping.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Who Talks About Flood Risks and Climate Change Adaptation? Analysis of Social Interactions in Three Countries.Risk analysis : an official publication of the Society for Risk Analysis · 2026Article
- Opinion Dynamic and Social Clustering in a 2D Space: An Agent Based Experiment.Computational economics · 2026Article
- A Dynamic Network Model of Societal Complexity and Resilience Inspired by Tainter's Theory of Collapse.Entropy (Basel, Switzerland) · 2024Article
- Integrating evolutionary theory and social-ecological systems research to address the sustainability challenges of the Anthropocene.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Review
- Dose-response functions and surrogate models for exploring social contagion in the Copenhagen Networks Study.The European physical journal. Special topics · 2021Article
- Reply to Smith et al.: Social tipping dynamics in a world constrained by conflicting interests.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
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Abstract
Social tipping, where minorities trigger larger populations to engage in collective action, has been suggested as one key aspect in addressing contemporary global challenges. Here, we refine Granovetter's widely acknowledged theoretical threshold model of collective behavior as a numerical modelling tool for understanding social tipping processes and resolve issues that so far have hindered such applications. Based on real-world observations and social movement theory, we group the population into certain or potential actors, such that - in contrast to its original formulation - the model predicts non-trivial final shares of acting individuals. Then, we use a network cascade model to explain and analytically derive that previously hypothesized broad threshold distributions emerge if individuals become active via social interaction. Thus, through intuitive parameters and low dimensionality our refined model is adaptable to explain the likelihood of engaging in collective behavior where social-tipping-like processes emerge as saddle-node bifurcations and hysteresis.
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