Sentiment analysis of Sina Weibo based on semantic sentiment space model

With the rapid development of Web 2.0, more and more people begin to publish information or their custom opinions on the Internet. Micro-blog´s application satisfies people´s need and provides a public platform for people to post and interact in real time. As a result of the rapidly increasing number of micro-blog updates, a lot of information and emotions complex data release in this platform, researches on micro-blog have attracted more and more attention, especially, one continuous heat topic, sentiment analysis of short message. So far, Chinese micro-blog exploration still needs lots of further work. Focus on Sina Weibo´s sentiment analysis, the key of this paper is to put forward three methods of Micro-Blog orientation classification to resolve the problem of Micro-Blog sentiment analysis, and compare the accuracy and performance of each classification method.