Community Discovery For Microblog Based On Complex Network Analysis

Microblog, as a new kind of social network platform, plays a significant role in China social networks. The microblog attracts amount of people due to the information’s rapidly diffuse, the real-time communication and the convenient of interaction. As the microblog users have different occupations or interests, the microblog network exists many different kinds of community.The purpose of microblog community discovery is to find the communities in a microblog network in which the users have the largest similarity among them. Obviously, techniques in data mining can be used in the network to detect the community structures in it. Scholars at home and abroad do lots of research about it and achieve some results. But with the development of internet and social network tools, people’s way of communication is changing, which makes many conventional algorithms be not suitable for new social network tools any longer. Conventional community discovery algorithms are generally based on either links or interests and don’t take limits of obtaining microblog users’ social information into consideration. As a result, they can’t detect multiple communities effectively. In such case, based on the analysis of existing algorithms of web communities discovery, this thesis focuses on microblog community discovery based on Label Propagation Algorithm. The main contents of this thesis are as follow:(1) Use Sina Weibo as an example, we discuss the microblog’s types, structure features and functions. Moreover, we also introduce the existing web community model, scale-free property, links and homogeneity.(2) We introduce and analyze the classical technologies of community detection and some basis methods for text mining.(3) For microblog, which is a widely used social media, we use the Label Propagation Algorithm as the foundation, after have an analysis of the topic relevancy between the nodes in a network and the probability of label propagation between the nodes, we propose an algorithm for microblog community discovery from the perspective of complex network analysis. Then do some experiments on a real Sina Weibo dataset. We compare our algorithm with two existed algorithms(GN Algorithm and Spectral Bisection Method). The experimental results show that our algorithm has a good performance on community discovery.