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

Ibrahim Abu Farha, Wajdi Zaghouani, Walid Magdy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 0.748F1PN respectively
Original languageEnglish
Title of host publicationProceedings of the Sixth Arabic Natural Language Processing Workshop
PublisherAssociation for Computational Linguistics (ACL)
Pages296-305
Number of pages10
ISBN (Print)978-1-954085-09-1
Publication statusPublished - 19 Apr 2021
EventThe Sixth Arabic Natural Language Processing Workshop - Virtual
Duration: 19 Apr 202119 Apr 2021
https://sites.google.com/view/wanlp2021

Workshop

WorkshopThe Sixth Arabic Natural Language Processing Workshop
Abbreviated titleWANLP 2021
Period19/04/2119/04/21
Internet address

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