ILSR rumor spreading model with degree in complex network

Abstract

Most rumors in social networks are extremely harmful and have a significant negative impact on social welfare. Therefore, exploring the laws of rumor propagation has been one of the hot topics in current researches. Most traditional rumor spreading models are based on infectious disease transmission models, such as SIR. Since the influence of individual differences and the network structure on rumor spreading are not considered, the rumor propagation process in complex networks can only be described in a coarse-grained manner. In this paper, we consider the role of different users in rumor propagation. Based on the degree of different nodes in the network, we design a new state transition function for each node and proposed a new rumor propagation ILSR model. Firstly, we analyze the model, calculate the equilibrium point and the basic reproductive number to prove the rationality of the model. Then experiments are performed in WS networks, BA scale-free networks and a real Facebook network to investigate the relationship between various nodes with time and the impact of network structure on rumor propagation, and the experimental results show the correctness and effectiveness of the model. It provides a reference for exploring the propagation law of rumors in complex networks and guiding and controlling the propagation of rumors.