Abstract: Search engine only returns the Web page set for the user queries, it needs the user refine useful knowledge from it; Social Network Search (SNS) directly provides people and their interest to users by using characters' social relations and common hobbies. However, the SNS mainly exists two unresolved problems. On the one hand, the SNS can't semantically understand user queries submitted by users. On the other hand, the SNS only provides people search and interest search, and confines query domains for users. Microblog has become an important platform for social network. To address these problems of information retrieval about microblog and provide more knowledge for user queries, this project researches knowledge graph construction and analysis based on the microblog community. The project focuses on five contents. (1)It researches concept extractions for the microblog community, and concepts have five types including people, things, locations, events and topics. (2)It researches relationships extractions for the microblog community. The relationships among concepts include collection types formed by combining two arbitrary types above concepts. (3)It researches knowledge graph construction, and the knowledge graph is a semantic network graph which takes concepts and relationships respectively as vertices and edges. (4)It researches knowledge graph analysis. It includes construction effect analysis, evolution characteristics and rules analysis and application effect analysis. (5)It researches the application interface and system based the knowledge graph.