Effects of individual popularity on information spreading in complex networks

Abstract

In real world, human activities often exhibit preferential selection mechanism based on the popularity of individuals. However, this mechanism is seldom taken into account by previous studies about spreading dynamics on networks. Thus in this work, an information spreading model is proposed by considering the preferential selection based on individuals’ current popularity, which is defined as the number of individuals’ cumulative contacts with informed neighbors. A mean-field theory is developed to analyze the spreading model. Through systematically studying the information spreading dynamics on uncorrelated configuration networks as well as real-world networks, we find that the popularity preference has great impacts on the information spreading. On the one hand, the information spreading is facilitated, i.e., a larger final prevalence of information and a smaller outbreak threshold, if nodes with low popularity are preferentially selected. In this situation, the effective contacts between informed nodes and susceptible nodes are increased, and nodes almost have uniform probabilities of obtaining the information. On the other hand, if nodes with high popularity are preferentially selected, the final prevalence of information is reduced, the outbreak threshold is increased, and even the information cannot outbreak. In addition, the heterogeneity of the degree distribution and the structure of real-world networks do not qualitatively affect the results. Our research can provide some theoretical supports for the promotion of spreading such as information, health related behaviors, and new products, etc.