@inproceedings{abuzayed-al-khalifa-2021-sarcasm,
title = "Sarcasm and Sentiment Detection In {A}rabic Tweets Using {BERT}-based Models and Data Augmentation",
author = "Abuzayed, Abeer and
Al-Khalifa, Hend",
editor = "Habash, Nizar and
Bouamor, Houda and
Hajj, Hazem and
Magdy, Walid and
Zaghouani, Wajdi and
Bougares, Fethi and
Tomeh, Nadi and
Abu Farha, Ibrahim and
Touileb, Samia",
booktitle = "Proceedings of the Sixth Arabic Natural Language Processing Workshop",
month = apr,
year = "2021",
address = "Kyiv, Ukraine (Virtual)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.wanlp-1.38",
pages = "312--317",
abstract = "In this paper, we describe our efforts on the shared task of sarcasm and sentiment detection in Arabic (Abu Farha et al., 2021). The shared task consists of two sub-tasks: Sarcasm Detection (Subtask 1) and Sentiment Analysis (Subtask 2). Our experiments were based on fine-tuning seven BERT-based models with data augmentation to solve the imbalanced data problem. For both tasks, the MARBERT BERT-based model with data augmentation outperformed other models with an increase of the F-score by 15{\%} for both tasks which shows the effectiveness of our approach.",
}
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%0 Conference Proceedings
%T Sarcasm and Sentiment Detection In Arabic Tweets Using BERT-based Models and Data Augmentation
%A Abuzayed, Abeer
%A Al-Khalifa, Hend
%Y Habash, Nizar
%Y Bouamor, Houda
%Y Hajj, Hazem
%Y Magdy, Walid
%Y Zaghouani, Wajdi
%Y Bougares, Fethi
%Y Tomeh, Nadi
%Y Abu Farha, Ibrahim
%Y Touileb, Samia
%S Proceedings of the Sixth Arabic Natural Language Processing Workshop
%D 2021
%8 April
%I Association for Computational Linguistics
%C Kyiv, Ukraine (Virtual)
%F abuzayed-al-khalifa-2021-sarcasm
%X In this paper, we describe our efforts on the shared task of sarcasm and sentiment detection in Arabic (Abu Farha et al., 2021). The shared task consists of two sub-tasks: Sarcasm Detection (Subtask 1) and Sentiment Analysis (Subtask 2). Our experiments were based on fine-tuning seven BERT-based models with data augmentation to solve the imbalanced data problem. For both tasks, the MARBERT BERT-based model with data augmentation outperformed other models with an increase of the F-score by 15% for both tasks which shows the effectiveness of our approach.
%U https://aclanthology.org/2021.wanlp-1.38
%P 312-317
Markdown (Informal)
[Sarcasm and Sentiment Detection In Arabic Tweets Using BERT-based Models and Data Augmentation](https://aclanthology.org/2021.wanlp-1.38) (Abuzayed & Al-Khalifa, WANLP 2021)
ACL