The interaction of multiple information on multiplex social networks

• Published in: Information sciences 2022-08, Vol.605, p.366-380
• Main Authors: Zhang, Hegui, Chen, Xiaolong, Peng, Yi, Kou, Gang, Wang, Ruijie
• Format: Article
• Language: English
• Subjects: Competitive spreading; Cooperative spreading; Coupled information diffusion; Multiplex network
• ISSN: 0020-0255; 1872-6291
• DOI: 10.1016/j.ins.2022.05.036

•A unified framework is proposed to study the interactive diffusion of multiple information under the coexistence of competition and cooperation on multiplex social networks.•The characteristics of the coupled dynamics of multiple information are analyzed by adopting the microscopic Markov method.•The theoretical diffusion threshold is derived by applying an adapted microscopic Markov chain method.•Numerical simulation reveals the coupled diffusion characteristics of multiple information by considering both the competition and the cooperation among them. Coupled information diffusion in complex networks has been widely studied in recent years. Nevertheless, current research mainly focuses on the interaction between each information pair. In this study, we investigate the interaction of multiple types of information on multiplex networks by considering both the competition and the cooperation among them. To study the dynamic characteristics theoretically, a microscopic Markov chain approach is used to reveal the co-evolution of multiple information. Through extensive simulations, the outbreak threshold is analyzed theoretically. The results reveal that the pairwise interaction between each information pair has an obvious impact on its final outbreak scale and the diffusion threshold. Interestingly, even information that has no direct impact on the target information can affect the diffusion of the target information through indirect effects. In addition, the inhibitory effect of the competitive information and the promotion effect of the cooperative information on the target information will reach equilibrium under specific parameter space conditions. We also conduct numerical simulations on three real multiplex social networks, including two large-scale networks. Current results are beneficial for us to further understand the coupled diffusion of multiple information on multiplex social networks.