Visualization Analysis Of Social Network

The emergency of Internet has brought great change to people's life,causing the change of the information transfermission.Typically,those applications which are on behalf of Social Networks are leading us towards a more deeper web2.0 era.Everyone in the social network equals to a data source,which means the amount of data will take on exponential growth as the growth of user.It is worth our noting that there hides a lot of useful information behind these information.Regarding this,it shows great significance to have a good study of social network.Of all the analytical method,visualization shows great significance.It depicts people's network as dotted line,and then analyze the central?density?the location of node of network by specific software.Currently,Gephi is more excellent than other softwares in observation,big data analysis and visualization.And hence,we will take use of Gephi as our tool to analyze social network.In views of the ineffective information of crawler,we will user the open platform of the website to excavate user and blog information efficiently.At the same time, it is strongly recommended to optimize the program to further improve efficiency.Secondly,in consideration of the poor performance of modern layout algorithm,this article puts forward a spectral clustering based on user classification.This layout algorithm can help contain the structure of network while visualizing it.Finally,seeing that the existing index to evaluate the influence of user is unsound,this article will put forward a set of index.Then,we will use the collected data to conduct experiment to extract important factors with the help of SPSS.In the subsequent experiment,we'll use scatterplot matrix to verify the rationality of the use of factor analysis.