Research On Link Prediction Of Social Network Information Dissemination Based On Information Association

In the flood of information today,the information on the Internet is all-encompassing,and the repetition,overload and distortion of information are quite serious.People are drowning in the ocean of online garbage,but it is often difficult to find truly valuable content.In a way,these messy,redundant and untrue information seriously affect the stability of information dissemination in social networks.How to use the existing information to predict the generation of new links in the network is not only a basic problem in network analysis,but also an important application of today's popular commercial social networking sites.In social networks,through effective link prediction algorithm,it is possible to better understand the reasons for the relationship between users on social networks,and can filter user nodes in the network based on the predicted results,and recommend the information of interest to users.This paper takes the relation between information in social networks as the object of study.On the basis of studying the influence factors of information association in social network,this paper focuses on the research of information dissemination link in social network.The main work and contributions are as follows: First of all,this paper introduces the background and significance of the research,and in combination with the existing link prediction research,it is pointed out that it is of great practical significance to study information dissemination link prediction from the perspective of information association.Secondly,this paper describes the information association phenomenon in the process of social network information dissemination from the aspects of information attribute,user behavior,cooperation and competition.On this basis,the connotation of informationassociation in social network is described,and establishes the expression model using information associated to the different form of vector space model and user interaction strength,Volterra Lotka-model.Then,this paper analyzes the factors that influence the stability of information association from three perspectives of information influence,accuracy of information and user dissemination context,and analyzes the coupling effects of these factors.Finally,based on the correlation of information and the influence factors of information correlation stability,a link prediction method based on multi-source information similarity(MISLP)is established.And the experimental data of Sina micro-blog are verified and analyzed.The research results of this paper not only provide new ideas for discovering potential user relationships in social networks,but also provide some guidance and reference to the formulation of precise marketing strategies.