关键词: 双向门控循环单元（BGRU）, 深度学习, 情感分析

Abstract: Social network is an indispensable part of social life, and the text sentiment analysis of social network has become a research hot topic of natural language processing. In view that deep learning technology can automatically build text features, people have proposed deep learning models such as CNN (convolutional neural network) and BLSTM (bidirectional long short-term memory) to solve text sentiment analysis, but there are still problems such as complicated structures or long training time. BGRU (bidirectional gated recurrent unit) can remember the context information of sequence, the structure is relatively simple and the training speed is fast. A Chinese text sentiment analysis method based on BGRU is proposed. This method firstly converts the text into a sequence of word vector. Then it obtains the text sentiment features through BGRU. Finally, the classifier identifies the text sentiment orientation. The experimental results on the ChnSentiCorp corpus achieve 90.61% of [F1] value. It is shown that this method is superior to CNN and BLSTM, etc. And training speed is 1.36 times higher than that of BLSTM.

Key words: bidirectional gated recurrent unit (BGRU), deep learning, sentiment analysis