Research On Information Propagation Mechanism Based On Evolutionary Game Theory

As an important medium for information dissemination,a large number of users conduct various social activities on social software every day,which provides an important way for the wide spread of information.Therefore,information dissemination has the characteristics of wide spread,short-term explosiveness and complex communication methods.Research on the mechanism of information dissemination in social networks,and explore the law of information dissemination,so as to provide ideas for information dissemination control.This paper mainly studies the following two aspects:People are considered to be bounded rational users in the process of social network information dissemination,thus different users will have different attitudes towards same information due to their social environment or other factors.As a kind of social attribute of bounded rational users,the attitude continuously was selected and updates in the process of interaction between nodes,which makes the behavioral game between the propagating subjects and affects the dissemination of information.Therefore,an information propagation model based on evolutionary game is proposed in this paper.First,from an individual perspective,the node's attitude update rules are defined according to non-Bayesian social learning rules.Secondly,the game matrix between nodes based on attitude values are established,and the information propagation model based on node attitude is established according to the evolution analysis paradigm.By solving the equilibrium solution of dynamic equations for both positive and negative attitudes,and analyzing the stability of the corresponding equilibrium points,the evolution mechanism of dynamic interaction between attitude nodes is obtained.Finally,combined with the SIS model,the impacts of different attitudes on information dissemination are analyzed.The validity of the proposed model is verified by numerical analysis and simulation experiments.It shows that the different attitudes of nodes play an important role in information dissemination.Effective control of information propagation is of great significance to the real society.First of all,this paper focuses on quantifying the internal factors of social relations and the external factors of user similarity to influence the node's behavior in the process of information dissemination strategy selection.Secondly,the public goods game model is used to describe the mass behavior of nodes to disseminate information.The game between nodes is used as the driving force to drive the evolution of the network and obtain the updated network.Finally,based on the perfect applicability of the strictly controllable theory to the complex network,the minimum control node required for the updated network and its set of driving nodes are calculated.The effectiveness of the control method in information dissemination is verified by experiments.