Based on SVM Tibetan Web Public Opinion Sentiment Classification

Abstract

Tibetan Web text has increased rapidly in recent years. According to mining and analyzing the data about user’s comments, we could identify the Sentimental tendency and evolution. Therefore we can better understand the user's behavior. Hot Tibetan public opinion analysis at the same time also can give enterprise, government and other institutions to provide important decision-making basis. The paper first describes SVM algorithm. Then the study of public opinion and target Tibetan Web Sentiment classification is defined and described, after that the paper gives the basic ideas and experimental research program. Finally, we summarize the achievements and shortcomings of Tibetan sentiment classification, as well as describe the challenges and the prospects of its development prospects.