A Fine-grained Sentiment Analysis Method Based on Dependency Tree and Graph Attention Network

Content Provider	Scilit
Author	Tan, Yejin Guo, Wangshu He, Jiawei Liu, Jian Xian, Ming
Copyright Year	2020
Description	Journal: Journal of Physics: Conference Series With the rapid development of the Internet, e-commerce and social media have continued to develop and grow. Merchants tend to better understand users’ attitudes and emotional tendencies through comments. As the number of user reviews increases, the previous sentiment analysis methods have highlighted the problems of high cost and high error rate. How to use more advanced methods to analyse comments has become an urgent problem to be solved. In order to solve the above problems, in this article, we propose a fine-grained sentiment analysis method based on dependency tree and graph neural network, which can help businesses and social network platforms to identify users’ sentiment tendencies and can be subsequently used in recommendation systems and public opinion analysis systems. The experimental results show that our scheme has achieved the best results.
Related Links	https://iopscience.iop.org/article/10.1088/1742-6596/1651/1/012173/pdf
ISSN	17426588
e-ISSN	17426596
DOI	10.1088/1742-6596/1651/1/012173
Journal	Journal of Physics: Conference Series
Issue Number	1
Volume Number	1651
Language	English
Publisher	IOP Publishing
Publisher Date	2020-11-01
Access Restriction	Open
Subject Keyword	Journal: Journal of Physics: Conference Series Sentiment Analysis Methods Based On Dependency Analysis Method Based Grained Sentiment Analysis
Content Type	Text
Resource Type	Article
Subject	Physics and Astronomy