Abstract: With the rapid growth of the number of microblog users, some emotions and opinions carried in microblog have a growing impact on the society, especially some negative emotions related to the personal safety of the public, which may affect the stability of the society. Therefore, it is of great significance to analyze the sentiment of microblog. The content of microblog sentiment analysis includes the acquisition of microblog corpus, the preprocessing of microblog corpus and the methods of sentiment analysis. The commonly used sentiment analysis methods include the method based on emotion dictionary, the method based on machine learning, and the method based on depth learning. With the widespread use of attention mechanism in NLP field, many researchers began to integrate attention mechanism into deep learning model for sentiment analysis, which greatly improves the accuracy of sentiment analysis. The BERT model proposed by Google is also based on attention mechanism essentially, which has made a breakthrough in the field of sentiment analysis.

Key words: public opinion on microblog, sentiment analysis, deep learning, attention mechanism, BERT