Language-oriented Sentiment Analysis based on the Grammar Structure and Improved Self-attention Network

摘要

In the businesses, the sentiment analysis makes the brands understanding the sentiment of their customers. They can know what people are saying, how they're saying it, and what they mean. There are many methods for sentiment analysis; however, they are not effective when were applied in Vietnamese language. In this paper, a method for Vietnamese sentiment analysis is studied based on the combining between the structure of Vietnamese language and the technique of natural language processing, self-attention with the Transformer architecture. Based on the analysing of the structure of a sentence, the transformer is used to process the word positions to determine the meaning of that sentence. The experimental results for Vietnamese sentiment analysis of our method is more effectively than others. Its accuracy and F-measure are more than 91% and its results are suitable to apply in practice for business intelligence.