Chinese short text sentiment classification method based on fields

The present invention discloses a Chinese short text sentiment classification method based on fields, which includes: data preprocessing of a short text including sentence segmentation, word segmentation, stop word filtration, and field division; construction of a field-oriented sentiment dictionary; extraction and matching of sentiment paths, extraction and polarity discrimination of candidates, and TF-IDF weight calculation of sentiment words by the field-oriented sentiment dictionary and using a corpus as a data set; sentimental characteristic extraction of the short text; and the corpus training or unknown sentiment types discrimination by a rand forest algorithm. Experiments show that the scheme provided by the present invention has high accuracy rate.