Combining Humor and Sarcasm for Improving Political Parody Detection

Xiao Ao, Danae Sanchez Villegas, Daniel Preotiuc-Pietro, Nikolaos Aletras


Abstract
Parody is a figurative device used for mimicking entities for comedic or critical purposes. Parody is intentionally humorous and often involves sarcasm. This paper explores jointly modelling these figurative tropes with the goal of improving performance of political parody detection in tweets. To this end, we present a multi-encoder model that combines three parallel encoders to enrich parody-specific representations with humor and sarcasm information. Experiments on a publicly available data set of political parody tweets demonstrate that our approach outperforms previous state-of-the-art methods.
Anthology ID:
2022.naacl-main.131
Volume:
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Month:
July
Year:
2022
Address:
Seattle, United States
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1800–1807
Language:
URL:
https://aclanthology.org/2022.naacl-main.131
DOI:
10.18653/v1/2022.naacl-main.131
Bibkey:
Cite (ACL):
Xiao Ao, Danae Sanchez Villegas, Daniel Preotiuc-Pietro, and Nikolaos Aletras. 2022. Combining Humor and Sarcasm for Improving Political Parody Detection. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 1800–1807, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
Combining Humor and Sarcasm for Improving Political Parody Detection (Ao et al., NAACL 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.naacl-main.131.pdf
Code
 iamoscar1/multi_encoder_model_for_political_parody_prediction