Epidemic spreading model based on social active degree in social networks

In this paper, an improved Susceptible-Infected-Susceptible (SIS) epidemic spreading model is proposed in order to provide a theoretical method to analyze and predict the spreading of diseases. This model is based on the following ideas: in social networks, the contact probability between nodes is decided by their social distances and their active degrees. The contact probability of two indirectly connected nodes is decided by the shortest path between them. Theoretical analysis and simulation experiment were conducted to evaluate the performance of this improved model. Because the proposed model is independent of the network structure, simulation experiments were done in several kinds of networks, namely the ER network, the random regular network, the WS small world network, and the BA scale-free network, in order to study the influences of certain factors have on the epidemic spreading, such as the social contact active degree, the network structure, the average degree, etc. This improved model provides an idea for studying the spreading rule of computer virus, attitudes, fashion styles and public opinions in social networks.