Public Opinion Propagation Model on Social Networks

This paper proposes a public opinion propagation model on social networks based on SEIR. This model consider impacts of the node degree, social networks peculiar dissemination rules and users´ habits, utilizes epidemiology and complex network theories, and establishes the dynamic evolution equations by building mathematical models of informed probability and disseminate probability. Simulation results show that pages of updating information can affect the propagation behavior of S, E nodes directly, the value of spread probability is the key impact factor of propagation velocity and scale. Additional, the number of infected nodes should be maintained at an appropriate range in order to make the maximum range of public opinion propagation.