AlexU-AL at SemEval-2022 Task 6: Detecting Sarcasm in Arabic Text Using Deep Learning Techniques
Aya Lotfy, Marwan Torki, Nagwa El-Makky · Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022) · 2022
Sarcasm detection is an important task in Natural Language Understanding.Sarcasm is a form of verbal irony that occurs when there is a discrepancy between the literal and intended meanings of an expression.In this paper, we use the tweets of the Arabic dataset provided by SemEval-2022 task 6 to train deep learning classifiers to solve the sub-tasks A and C associated with the dataset.Sub-task A is to determine if the tweet is sarcastic or not.For sub-task C, given a sarcastic text and its non-sarcastic rephrase, i.e. two texts that convey the same meaning, determine which is the sarcastic one.In our solution, we utilize finetuned MARBERT (Abdul-Mageed et al., 2021) model with an added single linear layer on top for classification.The proposed solution achieved 0.5076 F1-sarcastic in Arabic sub-task A, accuracy of 0.7450 and F-score of 0.7442 in Arabic sub-task C. We achieved the 2 nd and the 9 th places for Arabic sub-tasks A and C respectively.