关键词: 自然语言处理, 情感分析, 情感字典, 机器学习, 深度学习

Abstract: Aiming at the trend that text sentiment analysis has gradually become an important part of natural language processing, and in the field of systematic recommendation and acquisition of user sentiment information, as well as public opinion reference for the government and enterprises, compared and summarized the methods in the field of sentiment analysis by literature research. Firstly, literature investigation is carried out on the methods of sentiment analysis from the dimensions of time and method, then the main methods of sentiment analysis, application scenarios are summarized and compared. The advantages and disadvantages of each method are analyzed. According to the analysis results, in the face of different task scenarios, there are mainly three sentiment analysis methods: sentiment analysis based on emotion dictionary, sentiment analysis based on machine learning and sentiment analysis based on deep learning. The method based on multi-strategy mixture has become the trend of improvement. Literature investigation shows that there is still room for improvement in the techniques and methods of text sentiment analysis, and It is widely used in e-commerce, psychotherapy and public opinion monitoring.

Key words: natural language processing, sentiment analysis, emotional dictionary, machine learning, deep learning