关键词: 突发事件, 用户影响力, 突发词, 聚类

Abstract: Bursty topics detection on microblog is an import branch of online public opinion analysis, and has attracted much attention from international scholars. In this paper, a new approach of calculating users' influence was proposed based on the analysis of users' behavior characteristics. Combining the user influence with text features and propagation features, this paper defined a concept named Bursty which is used to judge if a word was a burst word. Being judged by Bursty, burst words can be extracted from microblog corpus. Hierarchical clustering algorithm was introduced to cluster the burst words and chose appropriate burst word clusters to describe bursty topics on microblog in order to realize bursty topics detection on microblog. In experiments, the precision, recall and F-measure reached 63.64%,87.5% and 74% respectively. The method is proved effective on bursty topic detection based on mass microblog data.

Key words: bursty topic, users' influence, burst word, clustering