Should a Chatbot be Sarcastic? Understanding User Preferences Towards Sarcasm Generation

Silviu Vlad Oprea, Steven Wilson, Walid Magdy


Abstract
Previous sarcasm generation research has focused on how to generate text that people perceive as sarcastic to create more human-like interactions. In this paper, we argue that we should first turn our attention to the question of when sarcasm should be generated, finding that humans consider sarcastic responses inappropriate to many input utterances. Next, we use a theory-driven framework for generating sarcastic responses, which allows us to control the linguistic devices included during generation. For each device, we investigate how much humans associate it with sarcasm, finding that pragmatic insincerity and emotional markers are devices crucial for making sarcasm recognisable.
Anthology ID:
2022.acl-long.530
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:
7686–7700
Language:
URL:
https://aclanthology.org/2022.acl-long.530
DOI:
10.18653/v1/2022.acl-long.530
Bibkey:
Cite (ACL):
Silviu Vlad Oprea, Steven Wilson, and Walid Magdy. 2022. Should a Chatbot be Sarcastic? Understanding User Preferences Towards Sarcasm Generation. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 7686–7700, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
Should a Chatbot be Sarcastic? Understanding User Preferences Towards Sarcasm Generation (Oprea et al., ACL 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.acl-long.530.pdf