metadata
language:
- en
https://github.com/EducationalTestingService/sarcasm
@inproceedings{ghosh-etal-2020-report,
title = "A Report on the 2020 Sarcasm Detection Shared Task",
author = "Ghosh, Debanjan and
Vajpayee, Avijit and
Muresan, Smaranda",
booktitle = "Proceedings of the Second Workshop on Figurative Language Processing",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.figlang-1.1",
doi = "10.18653/v1/2020.figlang-1.1",
pages = "1--11",
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.",
}