User behavior analysis based on edge evolutionary game model in social network

Abstract

The application of evolutionary game method to study user behavior in social networks is a current hot issue. Most of the current evolutionary game models are proposed based on the game between nodes, which cannot accurately describe the diverse behaviors of users, and ignores the influence of network dynamics on evolutionary game. In order to solve the above problems, an edge evolution game (EEG) model is proposed in this paper. Firstly, the edge game model combines the pairwise interaction mode with the prisoner’s dilemma payoff matrix to calculate the user income. Secondly, on the basis of strategy update, the disconnect–reconnect mechanism is proposed to promote the updating of user relationship. In this mechanism, nodes perform the disconnect–reconnect based on the incomes: the betrayal neighbor with the lowest incomes is disconnected, and the neighbor of the disconnected neighbor with the highest incomes is reconnected. Finally, three kinds of networks are selected for experimental verification. The experimental results show that the cooperation clusters are formed in all three kinds of networks, which greatly promote the cooperation evolution among users.