Blog Community Discovering Based On Social Network Analysis

Blog is a complicated collection of hypertext and expands with tremendous speed. Discovering and applying useful information of blogsphere is a challenging job. There are a lot of communities which have very important information in the Internet. Knowing these communities is helpful to understand the whole blogsphere and the whole web. Organizing Blog into communities has many advantages. With communities,users can navigate their interesting information,Internet service providers can arrange efficient ports,and manufacturers can find right consumers. Community also reflects sociality of Blog, because blogsphere is a social network.So far many approaches have been proposed for detecting and mining blog communities. One of them is finding and maintaining some communities by human effort. It is costly and difficult to update. Nevertheless, there are still many unknown and newly emerged communities. Therefore some approaches and technologies are raised to find blog communities automatically or semi-automatically. The method of community extraction consists of two categories, one is structure oriented, and the other is content oriented. They have different data processing and analyzing methods. The former uses links and relations between the nodes of the network and the latter analyzes the text content of the web pages to find communities. But both of the approaches are not good enough and miss some important information in the processing step. This field is still new and there remain still many problems. In this paper we try to combine the structure analysis and content analysis together to improve the crawling efficiency and analyzing performance. We also designed and conducted feasible experiments to support our method and the result turned out to be good.After discovering a community we proposed a method to detect frequently discussed topics in the Blog community. We get the topics by analyzing the keywords frequency, spatiotemporal distribution of posts and comments response features of the blog community. This is very useful and provides important information for further mining in the community.