Sentiment Analysis of Chinese Comments Based on Hybrid Vector Model
摘要
In order to solve the problem of insufficient expression of sentiment information in the TF-IDF model,this paper proposes the Senti model to extract the sentiment information in the text,including positive/negative sentiment words,negative words,transition words and adverbs of degree in the sentences.The sentiment function of punctuations in the sentences is considered herein,and the sentiment dictionary and semantic rules are used to extract sentiment information,thus generating the corresponding sentiment matrix.On this basis,the proposed model is spliced with the TF-IDF model to form a hybrid vector model.Experimental results show that compared with the TF-IDF alone,the hybrid vector model shows higher accuracy and better classification effect.