Influence Maximization Node Mining with Trust Propagation Mechanism

The issue of maximizing influence is one of the hot issues in the study of complex networks. It’s of great significance for understanding the dissemination mechanism of network information and controlling rumor. In recent years, based on the percolation theory, the problem of maximizing the node identification has attracted a lot of attention. However, this method does not consider the influence of the propagation of trust on the maximization of influence. This paper introduces the trust transfer function to depict the phenomenon that trust value and distrust value decreases and increase, respectively, and uses the percolation theory to solve the node joint propagation strength index to excavate the influencer. Experiments show that the proposed algorithm outperforms other heuristic benchmark algorithms.