| dc.description.abstract | Social network analysis is a methodology to collect, analyze, and display the community relationship under different scenarios, it utilizes varied techniques to measure the social information, user-generated content, and social interaction. The last few years have seen a great deal of work on social network analysis. Community detection and discovery particularly is the most popular filed, and it can find the hidden communities to further analysis, such as community recommendation. However, role identification is a difficult job for many social network applications. One of the difficulties is to maintain and utilize large amount of distinct roles. And we found that there are few studies of any kind have examined the influence of using concept hierarchy to social network abstraction. In this paper, we attempt to adapt fuzzy classification method and construct a hierarchy for role classification, in other words, we want to design a role classification methodology based on the documents which users are interested in, and attempts to form the role hierarchy automatically then analyzes it. We believe this approach can encourage the utilization of social roles by considering their identifiable features at different levels.
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