A Taxonomy of Empathetic Questions in Social Dialogs

Ekaterina Svikhnushina, Iuliana Voinea, Anuradha Welivita, Pearl Pu


Abstract
Effective question-asking is a crucial component of a successful conversational chatbot. It could help the bots manifest empathy and render the interaction more engaging by demonstrating attention to the speaker’s emotions. However, current dialog generation approaches do not model this subtle emotion regulation technique due to the lack of a taxonomy of questions and their purpose in social chitchat. To address this gap, we have developed an empathetic question taxonomy (EQT), with special attention paid to questions’ ability to capture communicative acts and their emotion-regulation intents. We further design a crowd-sourcing task to annotate a large subset of the EmpatheticDialogues dataset with the established labels. We use the crowd-annotated data to develop automatic labeling tools and produce labels for the whole dataset. Finally, we employ information visualization techniques to summarize co-occurrences of question acts and intents and their role in regulating interlocutor’s emotion. These results reveal important question-asking strategies in social dialogs. The EQT classification scheme can facilitate computational analysis of questions in datasets. More importantly, it can inform future efforts in empathetic question generation using neural or hybrid methods.
Anthology ID:
2022.acl-long.211
Volume:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
May
Year:
2022
Address:
Dublin, Ireland
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2952–2973
Language:
URL:
https://aclanthology.org/2022.acl-long.211
DOI:
10.18653/v1/2022.acl-long.211
Bibkey:
Cite (ACL):
Ekaterina Svikhnushina, Iuliana Voinea, Anuradha Welivita, and Pearl Pu. 2022. A Taxonomy of Empathetic Questions in Social Dialogs. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 2952–2973, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
A Taxonomy of Empathetic Questions in Social Dialogs (Svikhnushina et al., ACL 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.acl-long.211.pdf
Software:
 2022.acl-long.211.software.zip
Code
 sea94/eqt