SCEIRS information dissemination model based on rumor spreading in complex networks

Complex networks are currently being studied in many fields of science, and many natural systems can be described by them. The Internet and the brain, which are networks of routers and neurons, respectively, are examples of complex networks. There are also different types of complex networks, which can be referred to as scale free networks, small world networks and random networks. In this paper, an epidemic model of rumor spread in all three types of these networks is proposed. In this model, in addition to the existing cases (susceptible-infected-recovered), the rumor delay mechanism as well as the counter-attack mechanism have been added. The proposed model is presented as: Susceptible - Infected - Infected - Counterattack - Recovered - Susceptible (SECIRS). The methods of diffusion and decontamination for these three types of networks are compared. The simulation results are exactly in line with the theoretical analysis and show that in scale free networks, the spread of pollution is faster than the other two types. Pollution is lower and decontamination is faster.