A model for sentiment classification of chinese microblog based on parsing and theme extension

The main features of microblog include different lengths, divergence of its themes, and inclusion of special symbols. It's essential for building a comprehensive modeling method, which integrating dependency sentence analysis, domain knowledge and emotions to analyze sentiment of microblog in various aspects, such as society, entertainment, security. In this paper, a topic-oriented sentiment analysis model for Chinese microblog was proposed, this model covers data preprocessing, dependency sentence analysis, theme extension, domain knowledge and rules, dynamic adjustment of polarity of sentiment words and emotions. Through the experiments of Sina weibo data from three different domains, this method obtains high analytical accuracy under specific experimental environment.