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Classification-Based Opinion Formation Model Embedding Agents’ Psychological Traits

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Abstract

We propose an agent-based opinion formation model characterised by a two-fold novelty. First, we realistically assume that each agent cannot measure the opinion of its neighbours about a given statement with infinite resolution and accuracy, and hence it can only perceive the opinion of others as agreeing much more, or more, or comparably, or less, or much less (than itself) with that given statement. This leads to a classification-based rule for opinion update. Second, we consider three complementary agent traits suggested by significant sociological and psychological research: conformism, radicalism and stubbornness. We rely on World Values Survey data to show that the proposed model has the potential to predict the evolution of opinions in real life: the classification-based approach and complementary agent traits produce rich collective behaviours, such as polarisation, consensus, and clustering, which can yield predicted opinions similar to survey results.

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  • Carlos Andres Devia & Giulia Giordano, 2023. "Classification-Based Opinion Formation Model Embedding Agents’ Psychological Traits," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 26(3), pages 1-1.
  • Handle: RePEc:jas:jasssj:2022-51-4
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    1. Carlos Andrés Devia & Giulia Giordano, 2024. "Graphical analysis of agent-based opinion formation models," PLOS ONE, Public Library of Science, vol. 19(5), pages 1-27, May.

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