As a social platform for sharing information

amicro-blog generates millions of information daily. Thus

searching for wanted information is difficult. Tosolve this problem

this paper proposes a novel user-driven visual microblog search method. The method usesfeature words to model the user's interest and to obtain the relationship between words and users based on the model. To search a relevant micro-blog

the method first locates micro-bloggers who arerelevant to the keywords and then filters micro-blogs. The method extends the query via anattention-diverting algorithm. Finally

the relevant users and feature words are visualized on the basis oftheir degree of relevance. An interactive interface is provided to enable users to search micro-blogs that are relevant to the feature words or users that they are interested in. We show through a case studythat users can efficiently find specific information by observing the visualization results and further interacting with the visualization interface. We provide an efficient microblog search method that regardsmicro bloggers as a bridge to search for relevant microblogs and narrow down the search range. The proposed method also uses the attention-diverting algorithm to extend the query before the result is finally visualized. The proposed method is efficient and useful for users to find specific microblogs.