Sentiment Classification for Online Comments on Chinese News
With the development of network technology, all kinds of events will be shown up as news rapidly on the World Wide Web. Internet users read the news and some of them give their comments online. It is important for crisis public relations, government decision-making and news impact analysis to understanding the netizens comments on the news events. Due to the huge amount of news and comments on Web, its very difficult to collect and process them manually. This paper proposes the framework of a sentiment classification system for online comments on Chinese news, and discusses the implementation technologies of news comment collecting and classifying. Experimental research is also conducted, and the result shows that the Support Vector Machine (SVM) approach usually achieves better performance than k-nearest neighbor (Knn) approach.
sentiment classification comments support vector machine kNN
Wen Fan Shutao Sun
School of Computer Science, Communication University of China Beijing, P.R.China
国际会议
太原
英文
740-745
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）