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Opinion models, election data, and political theory.
Entropy 26:33 (2024)
A unifying setup for opinion models originating in statistical physics and stochastic opinion dynamics are developed and used to analyze election data. The results are interpreted in the light of political theory. We investigate the connection between Potts (Curie-Weiss) models and stochastic opinion models in the view of the Boltzmann distribution and stochastic Glauber dynamics. We particularly find that the q-voter model can be considered as a natural extension of the Zealot model, which is adapted by Lagrangian parameters. We also discuss weak and strong effects (also called extensive and nonextensive) continuum limits for the models. The results are used to compare the Curie-Weiss model, two q-voter models (weak and strong effects), and a reinforcement model (weak effects) in explaining electoral outcomes in four western democracies (United States, Great Britain, France, and Germany). We find that particularly the weak effects models are able to fit the data (Kolmogorov-Smirnov test) where the weak effects reinforcement model performs best (AIC). Additionally, we show how the institutional structure shapes the process of opinion formation. By focusing on the dynamics of opinion formation preceding the act of voting, the models discussed in this paper give insights both into the empirical explanation of elections as such, as well as important aspects of the theory of democracy. Therefore, this paper shows the usefulness of an interdisciplinary approach in studying real world political outcomes by using mathematical models.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Glauber Dynamics ; Potts Models ; Data Analysis And Model Comparison ; Elections ; Interdisciplinarity ; Opinion Dynamics ; Q-voter Model ; Reinforcement Model ; Voting Behavior ; Weak And Strong Effects Continuum Limit; Behavior; Genetics; Dynamics
e-ISSN
1099-4300
Journal
Entropy
Quellenangaben
Volume: 26,
Issue: 3,
Article Number: 33
Publisher
MDPI
Publishing Place
St Alban-anlage 66, Ch-4052 Basel, Switzerland
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Institute of Computational Biology (ICB)