Micro-Blog cyberspace is a booming multiple mode network of numerous overlapping communities covering huge amount of users and topics relating to the nature, the society and the everyday life. Based on in depth analysis on the entities and inherent relationships among the network, this paper purposes a user-topic relation dominated structural module for overlapping community representation and detection, and also infuses the follow relationship along with the blog-forward and blog-comment relationship into the module. By introducing a virtual community into the actual communities of the network, the paper also puts forward an improved global belongingness matrix as user's role representation which has the ability to properly describe a user's degree of participation and importance in the network. Experimental results on Sina's micro-blog dataset show that the new method is favorable and efficient for finding meaningful communities from the micro-blog. Furthermore, the proposed module and algorithms can be adapted in various ways for similar social network analysis and helpful for community evolution research.