@inproceedings{ao-etal-2022-combining,
title = "Combining Humor and Sarcasm for Improving Political Parody Detection",
author = "Ao, Xiao and
Sanchez Villegas, Danae and
Preotiuc-Pietro, Daniel and
Aletras, Nikolaos",
editor = "Carpuat, Marine and
de Marneffe, Marie-Catherine and
Meza Ruiz, Ivan Vladimir",
booktitle = "Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jul,
year = "2022",
address = "Seattle, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.naacl-main.131",
doi = "10.18653/v1/2022.naacl-main.131",
pages = "1800--1807",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Combining Humor and Sarcasm for Improving Political Parody Detection
%A Ao, Xiao
%A Sanchez Villegas, Danae
%A Preotiuc-Pietro, Daniel
%A Aletras, Nikolaos
%Y Carpuat, Marine
%Y de Marneffe, Marie-Catherine
%Y Meza Ruiz, Ivan Vladimir
%S Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, United States
%F ao-etal-2022-combining
%X 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.
%R 10.18653/v1/2022.naacl-main.131
%U https://aclanthology.org/2022.naacl-main.131
%U https://doi.org/10.18653/v1/2022.naacl-main.131
%P 1800-1807
Markdown (Informal)
[Combining Humor and Sarcasm for Improving Political Parody Detection](https://aclanthology.org/2022.naacl-main.131) (Ao et al., NAACL 2022)
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.