GOF at Arabic Hate Speech 2022: Breaking The Loss Function Convention For Data-Imbalanced Arabic Offensive Text Detection

Ali Mostafa, Omar Mohamed, Ali Ashraf

Abstract
With the rise of social media platforms, we need to ensure that all users have a secure online experience by eliminating and identifying offensive language and hate speech. Furthermore, detecting such content is challenging, particularly in the Arabic language, due to a number of challenges and limitations. In general, one of the most challenging issues in real-world datasets is long-tailed data distribution. We report our submission to the Offensive Language and hate-speech Detection shared task organized with the 5th Workshop on Open-Source Arabic Corpora and Processing Tools Arabic (OSACT5); in our approach, we focused on how to overcome such a problem by experimenting with alternative loss functions rather than using the traditional weighted cross-entropy loss. Finally, we evaluated various pre-trained deep learning models using the suggested loss functions to determine the optimal model. On the development and test sets, our final model achieved 86.97% and 85.17%, respectively.
Anthology ID:
2022.osact-1.21
Volume:
Proceedinsg of the 5th Workshop on Open-Source Arabic Corpora and Processing Tools with Shared Tasks on Qur'an QA and Fine-Grained Hate Speech Detection
Month:
June
Year:
2022
Address:
Marseille, France
Editors:
Hend Al-Khalifa, Tamer Elsayed, Hamdy Mubarak, Abdulmohsen Al-Thubaity, Walid Magdy, Kareem Darwish
Venue:
OSACT
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
167–175
Language:
URL:
https://aclanthology.org/2022.osact-1.21
DOI:
Bibkey:
Cite (ACL):
Ali Mostafa, Omar Mohamed, and Ali Ashraf. 2022. GOF at Arabic Hate Speech 2022: Breaking The Loss Function Convention For Data-Imbalanced Arabic Offensive Text Detection. In Proceedinsg of the 5th Workshop on Open-Source Arabic Corpora and Processing Tools with Shared Tasks on Qur'an QA and Fine-Grained Hate Speech Detection, pages 167–175, Marseille, France. European Language Resources Association.
Cite (Informal):
GOF at Arabic Hate Speech 2022: Breaking The Loss Function Convention For Data-Imbalanced Arabic Offensive Text Detection (Mostafa et al., OSACT 2022)
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