Sentiment Feature Selection from Chinese Online Reviews
Jiazhen Huo · 2012
Using statistical machine learning methods for sentiment classification of Chinese online reviews feature selection research.Select words,various combinations of words,N-gram as the potential sentimental feature.Use the Document Frequency to reduce dimensionality,adopt Boolean Weighting method to structure vectors and SVM classifier to classify online reviews.At last,have an experimental analysis based on online reviews of mobile phone.The results showed that:sentiment classification of Chinese online reviews will obtain the highest accuracy when taking adjectives, adverbs and verbs together as the feature.When taking N-gram as the feature,the results showed that low order Ngrarns can achieve a better performance than high order N-grams.Different training corpus size and feature size have distinct impact on classification,but not the more the better.