Coexistence of positive and negative information in information-epidemic dynamics on multiplex networks

Li-Ying Liu, Chao-Ran Cai, Si-Ping Zhang and Bin-Quan Li

Physica A: Statistical Mechanics and its Applications, 2025, vol. 666, issue C

Abstract: This paper investigates the coexistence of positive and negative information in the context of information-epidemic dynamics on multiplex networks. In accordance with the tenets of mean field theory, we present not only the analytic solution of the epidemic threshold, but also the coexistence conditions of two distinct forms of information (i.e., the two phase transition points at which a single form of information becomes extinct). In regions where multiple forms of information coexist, the infection curve follows two completely distinct patterns as the infection rate increases: a monotonic increase, and an initial increase followed by a subsequent decrease and re-increase. The physical mechanisms that give rise to these different patterns have also been elucidated. The theoretical results are robust with regard to the network structure and show a high degree of agreement with the findings of the Monte Carlo simulation.

Keywords: Information coexistence; Mean field theory; Microscopic Markov chain theory; Information-epidemic dynamics; Networks (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:666:y:2025:i:c:s0378437125001864

DOI: 10.1016/j.physa.2025.130534

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