A Report on the 2020 Sarcasm Detection Shared Task

Debanjan Ghosh, Avijit Vajpayee, Smaranda Muresan


Abstract
Detecting sarcasm and verbal irony is critical for understanding people’s actual sentiments and beliefs. Thus, the field of sarcasm analysis has become a popular research problem in natural language processing. As the community working on computational approaches for sarcasm detection is growing, it is imperative to conduct benchmarking studies to analyze the current state-of-the-art, facilitating progress in this area. We report on the shared task on sarcasm detection we conducted as a part of the 2nd Workshop on Figurative Language Processing (FigLang 2020) at ACL 2020.
Anthology ID:
2020.figlang-1.1
Volume:
Proceedings of the Second Workshop on Figurative Language Processing
Month:
July
Year:
2020
Address:
Online
Venues:
ACL | Fig-Lang | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1–11
Language:
URL:
https://aclanthology.org/2020.figlang-1.1
DOI:
10.18653/v1/2020.figlang-1.1
Bibkey:
Cite (ACL):
Debanjan Ghosh, Avijit Vajpayee, and Smaranda Muresan. 2020. A Report on the 2020 Sarcasm Detection Shared Task. In Proceedings of the Second Workshop on Figurative Language Processing, pages 1–11, Online. Association for Computational Linguistics.
Cite (Informal):
A Report on the 2020 Sarcasm Detection Shared Task (Ghosh et al., Fig-Lang 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.figlang-1.1.pdf
Video:
 http://slideslive.com/38929708