Research on university network public opinion sentiment analysis based on BERT and Bi-LSTM

Abstract

This paper proposes a method of emotion analysis based on BERT BiLSTM. Firstly, BERT is used to realize the word vectorization, and then Bilstm is constructed to extract semantic features for emotional analysis. In the experiment, the model designed in this paper is compared with the emotional dictionary, SVM, Word2vec LSTM, BERT TextCNN on the college online public opinion comment dataset, and the experiment proves that the accuracy of this model has been improved.