Researches On Mechanism Of Multiple Information Interaction In Social Networks

With the rapid development of Internet technology,social networks are becoming more and more popular,and people use social networks to express their opinions and make friends.Exploring the rule of information dissemination and maximizing information dissemination in social networks are hot areas of current research.However,most of the current research focuses on the study of independent information in a single network,ignoring the complex interactions between different information and the differences in the dissemination paths of different information.In real social networks,multiple information often exists at the same time and interacts with each other in the process of dissemination.Therefore,it is necessary to explore the mechanism of multiple information interaction.This thesis takes multiple information and multiplex networks as the research background.From the perspective of microscopic user behavior and heterogeneity of network structure,this thesis mainly studies the influence of the relationship between information and network topology structure on information spreading process.Based on the above,the problem of maximizing competitive information dissemination in multiplex network is explored.The main research work and contributions of this thesis are summarized as follows:1.Exploring the rule of multiple information dissemination in multiplex network from the perspective of microscopic user behavior.Firstly,considering the complex interaction between multiple information in social networks and the difference of dissemination paths between different information,and referring to SIS transmission mechanism,the model(MM-SIS)of information dissemination based on multiple information and multiplex networks is proposed.Secondly,the concept of “influence factor” is defined to express the complex and diverse interaction relationship between information,and to integrate the cooperation and competition between information into a unified model.Thirdly,from the perspective of user behavior,the dynamic equation of the MM-SIS model is constructed by using microscopic Markov chain method,which maps the microscopic user behavior to macroscopic spreading process of information.Finally,the mathematical method is used to analyze the information dissemination threshold in the MM-SIS model,and its accuracy is verified by experiments.2.Exploring the problem of maximizing competitive information dissemination in multiplex network from the perspective of network topology heterogeneity.Firstly,considering the heterogeneity of network structure,based on the MM-SIS model,the heterogeneous mean field theory is used to construct the dynamic equation for the dissemination of competitive information in multiplex network;Secondly,considering the individual differences of nodes,the NIC(Node Initialization Cost)algorithm is proposed to calculate the costs of information initializing different nodes in the network.Finally,from the two aspects of promoting self-dissemination and suppressing the dissemination of the other party,three strategies for maximizing fully competitive information dissemination under the condition of limited resources in the multiplex network are proposed.The above two models are tested on real networks and generated networks.The experimental results show that the interaction between information has a significant impact on the information spreading process,and further reveals the evolution rules of multiple information in multiplex network.At the same time,the strategies of maximizing competitive information dissemination proposed in this thesis have important reference significance for practical problems.