Deep Learning-Based Text Sentiment Analysis in Chinese International Promotion

Abstract

The importance of teaching Chinese as a foreign language has grown in tandem with the rapid advancement of China's politics and economy. The Chinese language's international promotion strategy has taken shape, and it has become a major cause for our country and nation. Under such a new situation, the content and form of Chinese cultural communication have taken on new characteristics. Foreign friends will use a variety of ways to express their emotions and attitudes toward the Chinese on the Internet, most of which are mainly text comments. Sentiment analysis of text comments can provide valuable emotional information for our Chinese international communication and promotion activities. Text sentiment analysis using deep learning algorithms has advanced considerably in recent years. For that purpose, this study proposes a bidirectional long- and short-term memory network, as well as a text sentiment analysis model with a self-attentive mechanism, and applies it to comments on Chinese language promotion. Experiments show that our model achieves a good recognition situation and has application value.