Sentiment analysis of Chinese micro-blog based on multi-feature and combined classification
Shibin Xiao · Journal of Beijing Information Science & Technology University · 2013
In order to improve the accuracy of sentiment analysis,verbs and adjectives in micro-blog texts are selected as features and a hierarchical structure-based approach to the decline of feature dimension is put forward.The method based on the emoticon is designed to calculate the feature polarity.On this basis,the position weight calculation method based on the feature polarity is proposed.Then the micro-blog texts are classified into three categories including positive,negative and neutral one by SVM.By combining Lexicon-based and SVM Machine Learning method,better accuracy of classification can be achieved.Experimental results show that the approach proposedto the sentiment classification of Chinese micro-blog is effective.