Effect of the social influence on topological properties of user-object bipartite networks

Social influence plays an important role in analyzing online users’ collective behaviorsSalganik et al., Science 311, 854 (2006)]. However, the effect of the socialinfluence from the viewpoint of theoretical model is missing. In this paper, by takinginto account the social influence and users’ preferences, we develop a theoretical modelto analyze the topological properties of user-object bipartite networks, including thedegree distribution, average nearest neighbor degree and the bipartite clusteringcoefficient, as well as topological properties of the original user-object networks andtheir unipartite projections. According to the users’ preferences and the global rankingeffect, we analyze the theoretical results for two benchmark data sets, Amazon andBookcrossing, which are approximately consistent with the empirical results. This worksuggests that this model is feasible to analyze topological properties of bipartitenetworks in terms of the social influence and the users’ preferences.