Key Techniques Of Microblogging Public Opinion Analysis System

With the rapid development of network public opinion, especially on mi-cro blog, the domain platform for people to express their opinions in public events has rapidly changed. Public opinion analysis has become a popular re-search direction.In this paper, we mainly focused on the retrieval system and burst event detection system in Microblogging environment, the main research includes the following three aspects:1. This paper first discusses current research in text retrieval and burst detection, and then introduces some classic retrieval model and burst detection algorithm.2. Implement a short text retrieval system based on microblogging corpus. For a given topic, This system use query expansion algorithm based on the word active force (WAF) and "twice retrieval" algorithm to returns micro blog that is not only high correlation and high timeliness. Finally, the algorithm was used in2011TREC Micro-blog Track, and achieved good results.3. Provide some optimizations for the classical burst detection algorithm base on automaton adapted to the context of the micro blog. The two main di-rections include:first, due to the differences between micro blog and traditional webpage, pre-processing and model parameters could be different. Second, fo-cus on topic clustering method. That included promotion of eigenvectors and introducing lexical characteristics based on the word active force to similarities between words. Finally, there are experiments verified the feasibility of the algorithm.