关键词: 微博, 话题检测, 复杂网络, 重叠社团发现

Abstract: Micro-blog topic detection has become the current research focuses. A micro-blog topics detection method based on overlap community detection is proposed. Raw micro-blog data will be preprocessed. After micro-blog content segmentation, topic words will be extracted with part of speech and temporal distribution. And edge is created between high relevance topic words to get a complex network. The concept of community independent modularity is introduced, and the overlap community is detected with the model of community independent modularity maximization; each community is taken as a micro-blog topic. The method of overlap community detection can solve the problem of low accurate rate of topic detecting caused by one or more keywords belonging to more than one topic. The experiments results show that the proposed method is feasible in micro-blog topic detection.

Key words: micro-blog, topic detection, complex network, overlap community detection