The Information Dissemination On Social Network Based On The Evolutionary Game

One major function of social networks is the dissemination of information such as news,comments,and rumors.The information passing from a sender to a receiver intrinsically involves both of them by considering their personalities,utility functions,and interaction rules which further determine their decisions of which topic to be diffused.To understand such human aspects of the topics dissemination,we propose a game theoretical model of the multi-topics diffusion mechanisms in a social network.Each individual in the network is considered as both sender and receiver,who transmits different topics taking into account their payoffs and personalities including knowledge,interest and authority.On the basis of the empirical research achievement,four types of participants who are “expert”(who prefers the information it knows),“hobbyist”(who prefers the information it likes),“herd”(who prefers the information the authority diffuses)and “common”(who has no preference)respectively,are introduced in this paper.Then we design a simulation experiment that integrates different networks,different types of participants and different game parameters.After analyzing several cases,we find that when the networks' average degree is low,each condition shows that once there are not a few topics which domain the network immediately,the evolutionary game will tend to be difficult to converge,except the “herd” in BA which almost converge quickly.In addition,we observe the simulation results in the network with different average degree.Then the results indicate that it takes short time to converge with a low or high degree,and it takes long when the degree is medium.However,the convergence time in BA is always short.And the impact of interest on the diffusion of information has a greater than knowledge.Finally,the dynamic network and the government intervention are introduced in our information dissemination game model.And several simulations have been done and the result shows that the dynamic networks and information dissemination will promote each other and governments need to spend much manpower and resources to effectively intervene in the dissemination of information.