Kang Du , Ruguo Fan , Dongxue Wang , Xiao Xie , Xiaoxia Xu , Jinchai Lin
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引用次数: 0
Abstract
With the widespread use of social media in modern society, the impact of rumor propagation on public opinion and social stability has become increasingly prominent. Investigating the dynamics of rumor propagation is crucial for developing effective rumor control strategies and mitigating the harmful effects of rumors. However, existing studies primarily focus on the effects of individual or media debunking mechanisms within a single-layer network framework, often assuming uniform time lag effects across different propagating entities and processes. To address these gaps, this paper aims to comprehensively examine both debunking mechanisms, along with different types of time lag effects arising from information collection, transmission, and clarification processes, to investigate how rumors and counter-rumors interact and spread within two-layer networks. We first develop a new rumor spreading model, the XYZ-SIDR model, which consists of seven states: susceptible, debunking, and removed media, as well as susceptible, infected, debunking, and removed individuals. We then calculate the basic reproduction number and establish the local and global asymptotic stability of the model’s equilibrium points. Similarly, we construct and analyze an SIDR spreading system without the media debunking mechanism, which serves as a comparison to understand the impact of the media debunking mechanism on rumor propagation. Additionally, we examine the XYZ-SIDR spreading system with different time lags, allowing us to explore the influence of time lags on rumor propagation. Finally, the stability of the XYZ-SIDR model is verified using numerical simulations, key factors influencing rumor propagation are explored, and a comparative analysis of the XYZ-SIDR model with the SIDR and SIR models is conducted.
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.