Overview of the WANLP 2021 Shared Task on Sarcasm and Sentiment Detection in Arabic

Ibrahim Abu Farha, Wajdi Zaghouani, Walid Magdy


Abstract
This paper provides an overview of the WANLP 2021 shared task on sarcasm and sentiment detection in Arabic. The shared task has two subtasks: sarcasm detection (subtask 1) and sentiment analysis (subtask 2). This shared task aims to promote and bring attention to Arabic sarcasm detection, which is crucial to improve the performance in other tasks such as sentiment analysis. The dataset used in this shared task, namely ArSarcasm-v2, consists of 15,548 tweets labelled for sarcasm, sentiment and dialect. We received 27 and 22 submissions for subtasks 1 and 2 respectively. Most of the approaches relied on using and fine-tuning pre-trained language models such as AraBERT and MARBERT. The top achieved results for the sarcasm detection and sentiment analysis tasks were 0.6225 F1-score and 0.748 F1-PN respectively.
Anthology ID:
2021.wanlp-1.36
Volume:
Proceedings of the Sixth Arabic Natural Language Processing Workshop
Month:
April
Year:
2021
Address:
Kyiv, Ukraine (Virtual)
Venues:
EACL | WANLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
296–305
Language:
URL:
https://aclanthology.org/2021.wanlp-1.36
DOI:
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/2021.wanlp-1.36.pdf
Code
 iabufarha/arsarcasm-v2