Modeling information propagation in high-order networks based on explicit–implicit relationship

Abstract

A high-order network model with explicit relationship, implicit relationship and hyper nodes is constructed based on the characteristics of social networks. Based on this model, the information propagation processes in a complete trust network and a non-complete trust network are analyzed. In particular, when studying the information propagation in non-complete trust networks, a multi-information propagation training credibility SIR (MPTC-SIR) model is designed. Each node carries credibility value through propagating train with MPTC-SIR model and then quantifies it as the trust probability of nodes to the information. Finally, the simulations about true and fake information propagation were implemented respectively on three different networks. The experimental results show that the designed network model is closer to reality. The information propagation scope is much wider in the high-order complete trust network, and the information demise is relatively slow. The fake information spreads faster in the high-order non-complete trust network. In general, the trend of “bad news has wings” was reflected. The propagation of true information is slow but it is lasted a long time than that of fake information. The propagation of fake information is just the opposite. The theory matches the physical world, and the research has very important practical significance.