Aspect Sentiment Classification with Document-level Sentiment Preference Modeling

Xiao Chen, Changlong Sun, Jingjing Wang, Shoushan Li, Luo Si, Min Zhang, Guodong Zhou


Abstract
In the literature, existing studies always consider Aspect Sentiment Classification (ASC) as an independent sentence-level classification problem aspect by aspect, which largely ignore the document-level sentiment preference information, though obviously such information is crucial for alleviating the information deficiency problem in ASC. In this paper, we explore two kinds of sentiment preference information inside a document, i.e., contextual sentiment consistency w.r.t. the same aspect (namely intra-aspect sentiment consistency) and contextual sentiment tendency w.r.t. all the related aspects (namely inter-aspect sentiment tendency). On the basis, we propose a Cooperative Graph Attention Networks (CoGAN) approach for cooperatively learning the aspect-related sentence representation. Specifically, two graph attention networks are leveraged to model above two kinds of document-level sentiment preference information respectively, followed by an interactive mechanism to integrate the two-fold preference. Detailed evaluation demonstrates the great advantage of the proposed approach to ASC over the state-of-the-art baselines. This justifies the importance of the document-level sentiment preference information to ASC and the effectiveness of our approach capturing such information.
Anthology ID:
2020.acl-main.338
Volume:
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Month:
July
Year:
2020
Address:
Online
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
3667–3677
Language:
URL:
https://aclanthology.org/2020.acl-main.338
DOI:
10.18653/v1/2020.acl-main.338
Bibkey:
Cite (ACL):
Xiao Chen, Changlong Sun, Jingjing Wang, Shoushan Li, Luo Si, Min Zhang, and Guodong Zhou. 2020. Aspect Sentiment Classification with Document-level Sentiment Preference Modeling. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 3667–3677, Online. Association for Computational Linguistics.
Cite (Informal):
Aspect Sentiment Classification with Document-level Sentiment Preference Modeling (Chen et al., ACL 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.acl-main.338.pdf
Video:
 http://slideslive.com/38929040