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DiaASQ: A Benchmark of Conversational Aspect-based Sentiment Quadruple Analysis

Bobo Li, Hao Fei, Fei Li, Yuhan Wu, Jinsong Zhang, Shengqiong Wu, Jingye Li, Yijiang Liu, Lizi Liao, Tat-Seng Chua, Donghong Ji


Abstract
The rapid development of aspect-based sentiment analysis (ABSA) within recent decades shows great potential for real-world society. The current ABSA works, however, are mostly limited to the scenario of a single text piece, leaving the study in dialogue contexts unexplored. To bridge the gap between fine-grained sentiment analysis and conversational opinion mining, in this work, we introduce a novel task of conversational aspect-based sentiment quadruple analysis, namely DiaASQ, aiming to detect the quadruple of target-aspect-opinion-sentiment in a dialogue. We manually construct a large-scale high-quality DiaASQ dataset in both Chinese and English languages. We deliberately develop a neural model to benchmark the task, which advances in effectively performing end-to-end quadruple prediction, and manages to incorporate rich dialogue-specific and discourse feature representations for better cross-utterance quadruple extraction. We hope the new benchmark will spur more advancements in the sentiment analysis community.
Anthology ID:
2023.findings-acl.849
Volume:
Findings of the Association for Computational Linguistics: ACL 2023
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Anna Rogers, Jordan Boyd-Graber, Naoaki Okazaki
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
13449–13467
Language:
URL:
https://aclanthology.org/2023.findings-acl.849
DOI:
10.18653/v1/2023.findings-acl.849
Bibkey:
Cite (ACL):
Bobo Li, Hao Fei, Fei Li, Yuhan Wu, Jinsong Zhang, Shengqiong Wu, Jingye Li, Yijiang Liu, Lizi Liao, Tat-Seng Chua, and Donghong Ji. 2023. DiaASQ: A Benchmark of Conversational Aspect-based Sentiment Quadruple Analysis. In Findings of the Association for Computational Linguistics: ACL 2023, pages 13449–13467, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
DiaASQ: A Benchmark of Conversational Aspect-based Sentiment Quadruple Analysis (Li et al., Findings 2023)
Copy Citation:
PDF:
https://aclanthology.org/2023.findings-acl.849.pdf
Video:
 https://aclanthology.org/2023.findings-acl.849.mp4