The invention discloses a topic detection and tracking method based on microblog data. In the method, potential hidden subjects in large-scale social network information are mined. The method comprises the following steps: firstly, partitioning microblog data increasing massively according to time sequence properties, and filtering redundant information; secondly, analyzing and classifying text contents in time windows, returning key subject descriptions with independent semantics after extraction, and extracting topics in different time windows; and lastly, analyzing the inheritance and the identity of topics among the time windows to conclude the variation tendency of microblog topics. According to the method, the dynamic developing process of topic contents, namely, the generation, development, climax and extinction of topics can be shown, and topics are described more accurately and fully.