The Trust Degree Evolution of Public Opinion Propagation in a Complex Network

A multi-community complex trust network evolution model is constructed and the fact that the minus value between the reward range and punishment range affects the trust degree of a complex trust network is made certain for the problem that the evolution of the trust weight value of the complex trust network being seldom considered. Firstly, a directed and weighted multi-community complex trust network model is built. Secondly, a new search algorithm of Poisson random walk visitor and a new model of propagation style with distinct attitude values of public opinion are established. Thirdly a method is designed for a node to select an opinion attitude value in accordance with the maximum trust value when two contradict attitude values are propagated to the node. Fourthly, the trust values of propagators are rewarded or punished after propagation. Finally, the model’s simulation is carried on for several times and the trend in the evolution of trust values is analyzed for each time. The results show the trust values are mainly affected by the minus value between the reward range and punishment range. When the minus value is larger, the mean trust values of the communities and the whole net are bigger and vice versa. If the minus value is zero, the mean trust values trend to be ups and downs. The study considers the propagation not only in the opposite attitude values, but also based on the trust, beyond the propagation characteristics of public opinion considered by other researchers. The results are in good agreement with the actual situation.