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In traditional models of opinion dynamics, each agent in a network has an opinion and changes in opinions arise from pairwise (i.e., dyadic) interactions between agents. However, in many situations, groups of individuals possess a collective opinion that can differ from the opinions of their constituent individuals. In this paper, we study the effects of group opinions on opinion dynamics. We formulate a hypergraph model in which both individual agents and groups of three agents have opinions, and we examine how opinions evolve through both dyadic interactions and group memberships. We find for some parameter values that the presence of group opinions can lead to oscillatory and excitable opinion dynamics. In the oscillatory regime, the mean opinion of the agents in a network has self-sustained oscillations. In the excitable regime, finite-size effects create large but short-lived opinion swings (as in social fads). We develop a mean-field approximation of our model and obtain good agreement with direct numerical simulations. We also show—both numerically and via our mean-field description—that oscillatory dynamics occur only when the numbers of dyadic and polyadic interactions of the agents are not completely correlated. Our results illustrate how polyadic structures, such as groups of agents, can have important effects on collective opinion dynamics.
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This content will become publicly available on August 1, 2026
Climate change and opinion dynamics models: Linking individual, social, and institutional-level change
Opinion dynamics models are increasingly used to understand changes in opinions, behaviors, and policy in the context of climate change. We review recent research that demonstrates how these models enable the linkages between individual, social, institutional, and biophysical factors to explain when and how social change emerges over time and what its impact might be on emissions and the climate system. We focus on applications of opinion dynamics models to climate change and describe how factors interact in those models to create feedback loops that reinforce or dampen change. We demonstrate how these models reveal the dynamics of consensus or polarization in climate opinions, the evolution of sustainability technologies and policies, and when and how interventions or negotiations related to climate change are likely to succeed or fail.
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- Award ID(s):
- 2436120
- PAR ID:
- 10638585
- Publisher / Repository:
- ScienceDirect
- Date Published:
- Journal Name:
- Current opinion in behavioral sciences
- ISSN:
- 2352-1546
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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