Fans’ Interest Mining Of Enterprise Microblog Based On The Supernetwork

Microblog is a new media product which based on the technology of Web2.0,and it is a kind of information dissemination and sharing platforms of social network. In daily life, the spread of the topic, the discussion of a hot issues and the network product sales is inseparable from Microblog. In recent years, domestic and foreign scholars began to study Microblog and the number of published literature grows quickly, but also it has attracted many researchers in other fields to join in. However, the study of Microblog is still in the development stage,and its research methods and content is not yet ripe.Due to the huge amount of date and the rapid expansion of information, people’s recognition on microblog is weakened.As Microblog is the representative of the virtual community, communication between users and the number of nodes to form a complex network of systems. General network can not fully express the relationship between topics and users. Therefore, we need to establish super network to solve the problem of the variety of topological properties. In this way, we can fully describe the two kinds of different quality point in Microblog.Fans, as a special group, often love something crazily. And Microblog fans are one of the online fans,who “follow”the micro bloggers,then he becomes its fans.The more fans a micro blogger has,the more are people likely to see it. We study the behavior of the fans,which can enhance the brand image of companies and the microblog marketing abilities,but also allows companies to know the user’s product experience situations. Currently,the research on the fans’ behavior is little,and the research about microblog fans’ behavior is less.First of all,we analysis the research status of microblog based on supernetwork,and learn from the existing supernetwork models.We propose the core body microblogging network,the fans’ sub-network and the fans interest supernetwork of the enterprise microblog.Then we have the microblog topics wordsegmentation,and each one can be extracted five key words that establishes connection between the microblog topics and the key words.Fans participate in microblog topics by discussions or taking comments,which establishes relationship with keywords indirectly.Finally,we use the C++ language to build a platform to capture the microblog data.And the data source is China Mobile official microblog.Meanwhile,we constructed the keywords’ network by the network model,but also we have word frequency analysis,centrality analysis and network cohesion analysis,which can verify the validity of the model.