“Laughing at you or with you”: The Role of Sarcasm in Shaping the Disagreement Space

Debanjan Ghosh, Ritvik Shrivastava, Smaranda Muresan


Abstract
Detecting arguments in online interactions is useful to understand how conflicts arise and get resolved. Users often use figurative language, such as sarcasm, either as persuasive devices or to attack the opponent by an ad hominem argument. To further our understanding of the role of sarcasm in shaping the disagreement space, we present a thorough experimental setup using a corpus annotated with both argumentative moves (agree/disagree) and sarcasm. We exploit joint modeling in terms of (a) applying discrete features that are useful in detecting sarcasm to the task of argumentative relation classification (agree/disagree/none), and (b) multitask learning for argumentative relation classification and sarcasm detection using deep learning architectures (e.g., dual Long Short-Term Memory (LSTM) with hierarchical attention and Transformer-based architectures). We demonstrate that modeling sarcasm improves the argumentative relation classification task (agree/disagree/none) in all setups.
Anthology ID:
2021.eacl-main.171
Volume:
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
Month:
April
Year:
2021
Address:
Online
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1998–2010
Language:
URL:
https://aclanthology.org/2021.eacl-main.171
DOI:
10.18653/v1/2021.eacl-main.171
Bibkey:
Cite (ACL):
Debanjan Ghosh, Ritvik Shrivastava, and Smaranda Muresan. 2021. “Laughing at you or with you”: The Role of Sarcasm in Shaping the Disagreement Space. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, pages 1998–2010, Online. Association for Computational Linguistics.
Cite (Informal):
“Laughing at you or with you”: The Role of Sarcasm in Shaping the Disagreement Space (Ghosh et al., EACL 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.eacl-main.171.pdf
Code
 ritvikshrivastava/multitask_transformers