角色分化高阶互动超图的社会传染

IF 3.1 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY
Juntao Lu , Jianlin Zhang , Qiang Xue , Siqi Zhao , Yanni Liu , Longqing Cui , Fanyuan Meng
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引用次数: 0

摘要

现有的复杂社会传染研究往往忽略了高阶结构中固有的角色分化。为了解决这一差距,我们引入了一个基于超图的传染模型,该模型明确区分了超边缘(群体)中的领导者和追随者角色。该模型包含关键参数:激活阈值,追随者影响权重,对称和非对称群体大小。我们推导了表征级联大小的自洽方程,并确定了与一阶相变相关的临界种子大小。我们的研究结果表明,追随者影响力的增加通过同伴强化增强了传染动力学,促进了由较小的初始种子发起的大规模级联。至关重要的是,涉及较小的对称领导-追随者群体大小的配置降低了临界种子大小。此外,由于结构异质性的增加,leader和follower群体大小服从泊松分布通常比固定大小的配置降低临界种子大小。这些发现为角色分化的高阶系统中的阈值驱动传染提供了基本理解,并为教育、营销和政治动员等领域的扩散过程建模提供了分析框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Social contagion on hypergraphs with role-differentiated higher-order interactions
Existing research on complex social contagion frequently neglects the role differentiation inherent in higher-order structures. To address this gap, we introduce a hypergraph-based contagion model that explicitly distinguishes between leader and follower roles within hyperedges (groups). The model incorporates key parameters: activation threshold, follower influence weight, and symmetric and asymmetric group sizes. We derive a self-consistency equation characterizing the cascade size and identify the critical seed sizes associated with first-order phase transitions. Our results demonstrate that increasing follower influence enhances contagion dynamics through peer reinforcement, facilitating large-scale cascades initiated by smaller initial seeds. Crucially, configurations involving smaller symmetric leader-follower group sizes reduce the critical seed size. Furthermore, distributions of leader and follower group sizes following Poisson distributions generally lower the critical seed size compared to fixed-size configurations, attributable to increased structural heterogeneity. These findings provide a basic understanding of threshold-driven contagion in role-differentiated, higher-order systems and provide an analytical framework for modeling diffusion processes in domains such as education, marketing, and political mobilization.
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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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