Sarcasm and Sentiment Detection In Arabic Tweets Using BERT-based Models and Data Augmentation

EACL (WANLP) 2021  ·  Abeer Abuzayed, Hend Al-Khalifa ·

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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