Text Emotion Classification from Reader Perspective

The past research of text emotion classification mainly face to the author's emotion.But this article classify texts'emotion from the reader's perspective.Using news articles as training sample sets,and using readers'vote information behind news articles as prior knowledge of the sample category.we put forward a semi-supervised classification model according to the incomplete data sets,the classification method using naive bayesian method and in couple with EM algorithm.Experiments show that our method is not only simple and effective,and has higher classification performance.