Design Of Data Visualization Platform Of Group Influence On Individual Based On Complex Network

With the rapid development of the Internet and information age,the scale of online social networks has grown rapidly,such as WeChat,weibo,BBS,etc.,which has been transformed from a refracting field of public opinion to a new trigger and outbreak pool.Therefore,it is extremely urgent to study the transmission mechanism of influence between nodes.However,most of the existing researches are about the transmission of influence between individuals,and few involve the influence of groups,let alone quantitative analysis.This paper summarizes and analyzes the advantages and disadvantages of the existing results.From different perspectives,it puts forward the algorithm of group's influence on individuals based on k-shell,contribution degree and intimacy degree,and carries out virus propagation simulation for the results.At last,this paper builds a data visualization platform based on the complex network.1.This paper summarizes the research situation of influence communication by domestic and foreign scholars,mainly introduces the application for influence transmission in different fields,analyzes the limitations of various methods,and expounds the common node importance measurement indexes in complex networks.Degree centrality,median centrality,k-shell and PageRank algorithm.Finally,several important virus transmission models are introduced,such as SI,SIR and SIS virus transmission models.2.Based on the current research situation and the existing research foundation,this paper regards the diffusion of node influence in the network as energy surging one layer at a time,combining K-Shell(K-shell)algorithm,and representing nodes.The contribution of the degree of mutual influence to the degree of interaction,taking into account the particularity of the social network,the intimacy factor is added to make the network more in line with the real social network,and then the influence propagation is further verified by simulation,and the influence of the group on the individual is obtained.Force algorithm.Finally,the paper quantitatively analyzes the individual influence transmission algorithm.3.Finally,a data visualization platform based on complex network is constructed.Firstly,data visualization and related technologies are introduced and compared.Then,a visualization platform for complex network data is designed and implemented based on the fundamental system requirements.Finally,various systems of the platform are tested.