Study On The Subgroup Of Academic Virtual Community Based On Complex Network

Academic virtual community has provided a quite more efficient mode of communication,whose share and transmission of knowledge make very effective complements in case of formal exchange. Reply relations represent a potential concern to reply object academic users in this community through each comment, which appears the certain pattern. It’s quite like the citation relationship that stands for the style of subject and approve of the view. This paper made analysis on academic virtual community based on the Scale-Free theory (Barabasi&Albert,1999), which is characterized by power law distribution. The foundation of Scale free network devised the people with certain relationship into point and lines and formed a complex network set which can analysis the relationship between point and point as well as point and subset to summarize the inner characteristic and the similarity. The relations among the users in this community consider the users as the nodes and the posting and replying as the relation lines. So it can easily get conclusions about the population through the study of subset which consists of most similar users. It is quite helpful to improve the information exchange and control inside a virtual academic community.This paper firstly summarized the development of complex network which start from the simple network, random network to more complex forms characterized by scale free and small world. It also studied the different definition and features for the academic virtual community and relative empirical and theoretical research. According to this paper, to get more detailed information in a professional forum, such as the top10topics and atmosphere of some subject, establishing a scale free network graph for the users and making socialized analysis could be a efficient way. The paper made research on the professional forum through the basic property of users, the times of replying, the characteristic of users from core areas and recognition of subset users based on the data drawn from the cancer medical BBS of Dingxiangyuan.After acquiring reply data, this paper established the scale free network based on the individual reply matrix and mutual reply matrix to study the control and power of the core users in the community in a quantitative way, which includes core-periphery analysis, k-core, hierarchical clustering method and Multidimensional Scaling as well as the users’ own reply information, identifications and so on. The subject in the forum can be categorized into four types:1) the newest paper’s posting and discussion on the cancer medical treatment.2) discussion on chemical treatment, including the medicine, molecular targeted therapy and some immunological methods.3) discussion on physicotherapeutics mainly about empirical experiment.4) Advisory on medical problem from nonmedical users.It can conclude that the separation is basically reasonable by comparing the subject with highest attention with identification. The results showed that applying the complex network into the research on the virtual academic forum is feasible. It is probable an innovation to apply the traditional network measurement method into the study user group from the perspective of replying and apply the cluster analysis and social network analysis with the visually information mining. At the meanwhile, this paper testified the result by the papers with highest attention and then analysis the information exchange and information share inside the cancer BBS.