Abstract:

Aiming at the sentiment classification for Chinese consumption comments, a method called two-dimensional coordinate mapping for sentiment classification based on corpus was constructed. According to the Chinese language characteristics, firstly, a more pertinent searching method based on corpus was proposed. Secondly, the rules of extracting the Chinese subjective phrases were defined. Thirdly, the choosing optimal seed words algorithm of the specific field was constructed. Finally, the two-dimensional coordinate mapping algorithm was constructed, which mapped the comment in two-dimensional Cartesian coordinates through calculating the coordinate values of the comment and decided the semantic orientation of it. Experiments were conducted on 1200 comments of milk (half of them are positive or negative comments) in Amazon. In the experiments, word “henhao-lou” was chosen as the optimal seed word by using choosing optimal seed words algorithm, then the sentiment orientation of it was decided according to two-dimensional coordinate mapping algorithm. The average F-measure of the proposed algorithm reached more than 85%. The result shows that the proposed algorithm can classify the sentiment of Chinese consumption comments.