TEXT SENTIMENT CLASSIFICATION METHOD, STORAGE MEDIUM AND COMPUTER

摘要

A text sentiment classification method, a storage medium and a computer. Said method comprises the following steps: constructing a sentiment dictionary for input text, the step of constructing a sentiment dictionary comprising selecting and expressing parts of speech, extracting base-level feature vectors; extracting mid-level features, and in combination with the sentiment dictionary, acquiring word vectors of training samples and pooling the word vectors of the training samples, so as to obtain mid-level feature vectors; performing weighted fusion on the base-level feature vectors and the mid-level feature vectors, so as to obtain fused feature vectors; calculating a classification result on the basis of a base-level feature vector classification model, a mid-level feature vector classification model and a fused feature vector classification model. The present invention solves the problem in the prior art that the sentiment classification is not efficient and stable enough.