Narrow Results

A new model of human flesh search (HFS) was established based on the love-triangle model (LTM) and susceptible-infected-recovered (SIR) model. The competitive propagation process between rumors and true messages in HFS was investigated. According to the proposed model, the equation was derived to describe the propagation of rumors and true messages in HFS. Coupling effect of rumors and true messages and the node credibility were considered; the simulations were implemented on small world network. The results show that the competition probability initial value of rumors is higher than that of true messages in the process of HFS. The coupling effect indicates that the spreading of one information fragment would be influenced by others. Furthermore, the inhibition of credibility on rumor spreading is found. Therefore, the means of suppressing rumors is proposed furtherly. Finally, the validity of the new model was verified through the comparative experiment between the simulation of the proposed model and real case.

In this paper, a two-layer network on various immunization strategies in the post-epidemic era is constructed and an improved symbiotic evolutionary model of COVID-19 and information collaboration is proposed. The dynamic transformation probability is introduced to influence the virus information transmission coevolutionary process. The dynamic transformation probability is influenced by the immunization strategies and vertex characteristics. We quantify the effects of immunization strategy, node properties, global temperature, and collaborative information dissemination on new crown outbreaks. We simulated our model in a scale-free network to analyze the propagation. The evolutionary phenomenon of the network during propagation was investigated. We simulated the proven epidemic information coevolutionary model in a two-layer network, validated it with real data comparisons by proving that our proposed model fits the real situation.