Application And Research Of Social Network Analysis Method In Technology Virtual Community

With the development of the Internet, especially the rise of mobile Internet, it affects every aspect of our lives by an amazing speed and an unusual breadth. Now it plays very important role in our learning and daily life. As a new kind of media, an advanced communication tools, a highly effective information summary and an active social platform. Network is changing our ways of communications、thinking and learning styles quietly. A long with the rapid development of computer network technology, the content of science and technology of the virtual world was improved constantly. The purpose of "zero distance, no limit" learning was come true by using Network. And micro-blog provides a platform which can be used to publish or query information to members of virtual community. At the same time, every member of virtual community and members who has been concerned about the public Weibo provided by community can publish some information at the platform. They also can read articles released by other members and share all kinds of learning resources etc.In the technology of virtual community, any member can express their views on a problem through micro-blog platform. Some members will respond in the first time. So the interactions with other members were formed. Communication with other members can be achieved. And it is beneficial for establishing social Internet in Weibo platform belongs to virtual community. It is convenient for our researching.First of all, the interactive relationship between members of a virtual community according to Hadoop technology was studied in this paper. Using the theory of social network to analyze social matrix in social network.Overall network characteristics of the network are the main computing. Such as: the network density, average radius, connectivity, such as central index, phenomenon of verifying whether the network to meet the "small world phenomenon", on the basis of overall network to analyze the subgroup of network. In addition, on the basis of the analysis of various nodes in the network structure, divide user group was realized by using the clustering algorithm. To study the quantity of individual fans in the social net was followed. Proving the fans of user whether obey to specific power-law distribution, statistically rigorous inspection is given.Secondly, compute the influence of index calculation of each user in the network. At same time network individual characteristics was researched. Because the Page Rank algorithm is mainly used for each page in the Internet, it is also used to measure degree of important of the specific Webpage. When Page Rank algorithm was applied to compute the users’ impact indicators in the micro-blog environment, the reasonable accurate results may be missed. Because this algorithm does not take into account some character is tics of users. Such as: the time of establishing microblog, the quantity of issued blog land the time of “points like”. Therefore, based on the original Page Rank algorithm, combined with some character is tics of micro-blog network put forward new user influence ranking model-Influence-Index. And establish a new transfer matrix model which meet the relevant assumptions Ma Kopf chain, thus making the strict theory support.Finally, the model is validated by experiment and result analysis through detailed analysis and comparison. Validating user influence of the new algorithm weather fully considers the characteristics of micro-blog network. Through this way, shortcoming of Page Rank algorithm in micro-blog network can be avoided effectively. And it is more comprehensive and more objective.