The interaction of multiple information on multiplex social networks
Hegui Zhang, Xiaolong Chen, Peng Yi, Gang Kou, Ruijie Wang
Abstract
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.