{"title":"Social contagion models on adaptive simplicial complexes","authors":"Ziting Luo , Shuai Li , Zheng Jiang , Wei Chen","doi":"10.1016/j.physa.2025.131010","DOIUrl":null,"url":null,"abstract":"<div><div>Complex networks, composed of nodes and edges connecting them, are successful in modeling various social contagion phenomena, such as epidemic spreading or rumor diffusion in population. Recently, there is extensive interest in studying higher-order interactions which uncover the complex mechanisms of influence and reinforcement in social contagion. Yet, existing models are primarily within the framework of static networks. Here we investigate the susceptible–infected–susceptible model on adaptive simplicial complexes, in which the networks exhibiting high-order structure can change their connectivity with time depending on their dynamical state. By applying mean-field equations, we derive an implicit analytical expression of the invasion threshold in adaptive simplicial complexes, but explicit expressions of the invasion threshold in three prototypical adaptive networks. We further analyze the effects of the transmission rate, the rewiring rate and higher-order interactions on epidemic prevalence and the invasion threshold. Our model can lead to collective phenomena including first-order phase transition, bistability, and hysteresis loops. Our study paves the way to predict and control a wide variety of social contagion processes on networks.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"679 ","pages":"Article 131010"},"PeriodicalIF":3.1000,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physica A: Statistical Mechanics and its Applications","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0378437125006624","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHYSICS, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Complex networks, composed of nodes and edges connecting them, are successful in modeling various social contagion phenomena, such as epidemic spreading or rumor diffusion in population. Recently, there is extensive interest in studying higher-order interactions which uncover the complex mechanisms of influence and reinforcement in social contagion. Yet, existing models are primarily within the framework of static networks. Here we investigate the susceptible–infected–susceptible model on adaptive simplicial complexes, in which the networks exhibiting high-order structure can change their connectivity with time depending on their dynamical state. By applying mean-field equations, we derive an implicit analytical expression of the invasion threshold in adaptive simplicial complexes, but explicit expressions of the invasion threshold in three prototypical adaptive networks. We further analyze the effects of the transmission rate, the rewiring rate and higher-order interactions on epidemic prevalence and the invasion threshold. Our model can lead to collective phenomena including first-order phase transition, bistability, and hysteresis loops. Our study paves the way to predict and control a wide variety of social contagion processes on networks.
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.