Abstract: The popularity of microblogging brings another form of social news media. The paper proposed an approach of news topics mining from microblog. News topics were formed by finding the emerging keywords in large numbers and clustering them. To extract news keywords,a compound weight was introduced combining the word frequency and the growth, to measure the likelihood of a word to be a news keyword, and to construct the topic, contextual relevance model was used to support incremental clustering, which is more suitable to the problem compared with semantic similarity. The experiments on real world microblog data show the effectiveness of the approach to detect news topic out of massroc mcssagcs.

Key words: Microblog,News,Topic detection,Clustering