The competitive information spreading over multiplex social networks

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

7 Scopus Citations
View graph of relations

Related Research Unit(s)


Original languageEnglish
Pages (from-to)981-990
Journal / PublicationPhysica A: Statistical Mechanics and its Applications
Online publishedAug 2018
Publication statusPublished - 1 Aug 2018


It is evident that social networks have become major information sources as well as the most effective platform for information exchange. In social networks, the dynamical propagation of different information often exhibits different dynamical behaviors. And different information may even compete with each other that can determine the dynamical process of information dissemination. These phenomena have led to the present study on the spreading process of competitive information over social networks. In this study, we proposed a competitive information model over the multiplex networks. The simulations of this model are verified by two types of the multiplex networks, such as the real composite network and the artificial composite network. Through controlling the spreading parameters in extensive large-scale simulations, it is found that the final density of stiflers increases with the growth of the spreading rate, while it declines with the increasing of the removal rate. It is also found that the spreading process of the competitive information is closely related to the node degrees on multiplex networks. Through controlling the exchanging rate of competitive information, we are able to determine information dominance accurately. Our new findings validate that the proposed model is capable of characterizing the dynamic evolution of competitive information over multiplex social networks. The results of this study are significant to the study of social science and social platform behavior.

Research Area(s)

  • Artificial composite network, Competitive information, Information propagation, Multiplex networks, Real composite network