Seeking Common but Distinguishing Difference, A Joint Aspect-based Sentiment Analysis Model

Hongjiang Jing, Zuchao Li, Hai Zhao, Shu Jiang


Abstract
Aspect-based sentiment analysis (ABSA) task consists of three typical subtasks: aspect term extraction, opinion term extraction, and sentiment polarity classification. These three subtasks are usually performed jointly to save resources and reduce the error propagation in the pipeline. However, most of the existing joint models only focus on the benefits of encoder sharing between subtasks but ignore the difference. Therefore, we propose a joint ABSA model, which not only enjoys the benefits of encoder sharing but also focuses on the difference to improve the effectiveness of the model. In detail, we introduce a dual-encoder design, in which a pair encoder especially focuses on candidate aspect-opinion pair classification, and the original encoder keeps attention on sequence labeling. Empirical results show that our proposed model shows robustness and significantly outperforms the previous state-of-the-art on four benchmark datasets.
Anthology ID:
2021.emnlp-main.318
Original:
2021.emnlp-main.318v1
Version 2:
2021.emnlp-main.318v2
Version 3:
2021.emnlp-main.318v3
Volume:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Month:
November
Year:
2021
Address:
Online and Punta Cana, Dominican Republic
Editors:
Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
3910–3922
Language:
URL:
https://aclanthology.org/2021.emnlp-main.318
DOI:
10.18653/v1/2021.emnlp-main.318
Bibkey:
Cite (ACL):
Hongjiang Jing, Zuchao Li, Hai Zhao, and Shu Jiang. 2021. Seeking Common but Distinguishing Difference, A Joint Aspect-based Sentiment Analysis Model. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 3910–3922, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
Seeking Common but Distinguishing Difference, A Joint Aspect-based Sentiment Analysis Model (Jing et al., EMNLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.emnlp-main.318.pdf
Video:
 https://aclanthology.org/2021.emnlp-main.318.mp4
Code
 betahj/pairabsa
Data
ASTEASTE-Data-V2