Abstract
This paper used three machine learning algorithms, three kinds of feature selection methods and three feature weight methods to study the sentiment classification for Chinese microblogging. The experimental results indicate that the performance of SVM is best in three machine learning algorithms; IG is the better feature selection method compared to the other methods, and TF-IDF is best fit for the sentiment classification in Chinese microblogging. Combining the three factors the conclusion can be drawn that the performance of combination of SVM, IG and TF-IDF is best.
Recommended Citation
Liu, Zhiming; Liu, Lu; and Li, Hong, "An Empirical Study of Sentiment Analysis for Chinese Microblogging" (2012). WHICEB 2012 PROCEEDINGS. 57.
https://aisel.aisnet.org/whiceb2011/57