Research Methods and Progress of Text Sentiment Analysis Based on Machine Learning

Abstract

With continuous development of artificial intelligence, Natural Language Processing (NLP) has become an emerging research field. As an important branch of NLP, text sentiment analysis has drawn attention from many scholars. At present, the mainstream methods of text sentiment analysis include text sentiment analysis method based on sentiment dictionary, machine learning, deep learning, and mixed strategy. The method based on the sentiment dictionary is no longer commonly used because it requires a lot of manual annotation. Due to traditional machine learning methods cannot perform good classification and prediction of context semantics, but deep learning can solve this problem, more and more researches will adopt a combination of the two methods. By investigating the current research at home and abroad, this paper describes and compares the aforementioned four methods in detail, summarizing their advantages and disadvantages, and proposing possible challenges in future research.