ArticleComputational economics2026
Opinion Dynamic and Social Clustering in a 2D Space: An Agent Based Experiment.
Article in Computational economics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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Authors and funding
3 authors.
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Abstract
This paper studies the impact of movement and interactions of individuals on opinion dynamics and polarisation within a two-dimensional (2D) space. By extending the Attraction-Repulsion Model (ARM), we explore how agents form opinion clusters based on geographic constraints and social interactions. Our model illustrates that individuals with similar opinions tend to form like-minded groups, with higher visibility leading to fewer, larger clusters. Conversely, low tolerance drives high polarisation. Geographic constraints result in larger clusters centralising to avoid conflicts, while smaller clusters remain peripheral. Additionally, as the number of opinion dimensions increases, fewer clusters form, indicating that a broader range of opinions leads to fewer, larger groups. This study provides insights into the feedback loop between agent movements and opinion polarisation, providing insights on the mechanisms behind social segregation and the formation of echo chambers. Furthermore, these findings are crucial for understanding and addressing societal issues such as political polarisation, misinformation spread, and the dynamics of social cohesion. Our research contributes to the field of opinion dynamics by highlighting the significant role of physical space and movement in shaping collective opinions and social structures, offering a comprehensive framework for future studies on the interplay between mobility, opinion formation, and polarisation.
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