A modified Hegselmann–Krause model for interacting voters and political parties

IF 3.1 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY Physica A: Statistical Mechanics and its Applications Pub Date : 2025-05-01 Epub Date: 2025-03-07 DOI:10.1016/j.physa.2025.130490
Patrick Cahill, Georg A. Gottwald
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Abstract

The Hegselmann–Krause model is a prototypical model for opinion dynamics. It models the stochastic time evolution of an agent’s or voter’s opinion in response to the opinion of other like-minded agents. The Hegselmann–Krause model only considers the opinions of voters; we extend it here by incorporating the dynamics of political parties which influence and are influenced by the voters. We show in numerical simulations for 1- and 2-dimensional opinion spaces that, as for the original Hegselmann–Krause model, the modified model exhibits opinion cluster formation as well as a phase transition from disagreement to consensus. We provide an analytical sufficient condition for the formation of unanimous consensus in which voters and parties collapse to the same point in opinion space in the deterministic case. Using mean-field theory, we further derive an approximation for the critical noise strength delineating consensus from non-consensus in the stochastically driven modified Hegselmann–Krause model. We compare our analytical findings with simulations of the modified Hegselmann–Krause model.
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选民与政党互动的修正Hegselmann-Krause模型
Hegselmann-Krause模型是一个典型的意见动力学模型。它模拟了一个代理人或选民的意见随其他志同道合的代理人意见的随机时间演变。Hegselmann-Krause模型只考虑选民的意见;我们在此加以扩展,纳入影响选民和受选民影响的政党的动态。我们在1维和2维意见空间的数值模拟中表明,与原始Hegselmann-Krause模型一样,修改后的模型显示意见聚类形成以及从分歧到共识的阶段转变。我们提供了在确定性情况下,选民和政党在意见空间崩溃到同一点的一致共识形成的分析充分条件。利用平均场理论,我们进一步推导了随机驱动修正Hegselmann-Krause模型中描述一致性和非一致性的临界噪声强度的近似。我们将我们的分析结果与修正的Hegselmann-Krause模型的模拟结果进行了比较。
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来源期刊
CiteScore
7.20
自引率
9.10%
发文量
852
审稿时长
6.6 months
期刊介绍: Physica A: Statistical Mechanics and its Applications Recognized by the European Physical Society Physica A publishes research in the field of statistical mechanics and its applications. Statistical mechanics sets out to explain the behaviour of macroscopic systems by studying the statistical properties of their microscopic constituents. Applications of the techniques of statistical mechanics are widespread, and include: applications to physical systems such as solids, liquids and gases; applications to chemical and biological systems (colloids, interfaces, complex fluids, polymers and biopolymers, cell physics); and other interdisciplinary applications to for instance biological, economical and sociological systems.
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