Sentiment analysis is part of the field of natural language processing (NLP), and its purpose is to dig out the process of emotional tendencies by analyzing some subjective texts. With the development of word vector, deep learning develops rapidly in natural language processing. Therefore, the text emotion analysis based on deep learning has also been widely studied. This article is mainly divided into two parts. The first part briefly introduces the traditional methods of sentiment analysis. The second part introduces several typical methods of sentiment analysis based on deep learning. The advantages and disadvantages of sentiment analysis are summarized and analyzed, which lays a foundation for the in-depth research of scholars.