Abstract / Description of output
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.
Original language | English |
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Title of host publication | Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) |
Subtitle of host publication | Proceedings of the Conference, Vol. 1 (Long Papers) |
Editors | Smaranda Muresan, Preslav Nakov, Aline Villavicencio |
Publisher | Association for Computational Linguistics |
Pages | 7686-7700 |
Number of pages | 15 |
Volume | 1 |
ISBN (Print) | 978-1-955917-21-6 |
Publication status | Published - 16 May 2022 |
Event | 60th Annual Meeting of the Association for Computational Linguistics - The Convention Centre Dublin, Dublin, Ireland Duration: 22 May 2022 → 27 May 2022 https://www.2022.aclweb.org |
Conference
Conference | 60th Annual Meeting of the Association for Computational Linguistics |
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Abbreviated title | ACL 2022 |
Country/Territory | Ireland |
City | Dublin |
Period | 22/05/22 → 27/05/22 |
Internet address |