Research on Sentiment Classification of Chinese Reviews Based on SVM

Sentiment classification is a classification technology which has many useful applications.to a certain extend,it can solve the clutter of network reviews,in order to facilitate the users to precisely define the necessary information.Up to now,most research of sentiment clas-sification is on English reviews,and little work has been done on Chinese reviews.In this paper,we will introduce how to apply SVM to solve sentiment classification problems.Its main target is to determine whether the reviews is positive or negative.In this paper,we will select the words which have semantic orientation as fetures,and use TF-IDF as the fetures presence vectors.This is the innovation of this article.The experimental results show that the method achieves an high accuracy rate when used to evaluate reviews from internet.