BFCAI at SemEval-2022 Task 6: Multi-Layer Perceptron for Sarcasm Detection in Arabic Texts

• URL: http://arxiv.org/abs/2205.08868v1
• Date: Wed, 18 May 2022 11:33:07 GMT
• Title: BFCAI at SemEval-2022 Task 6: Multi-Layer Perceptron for Sarcasm Detection in Arabic Texts
• Authors: Nsrin Ashraf and Fathy Elkazaz and Mohamed Taha and Hamada Nayel and Tarek Elshishtawy
• Abstract summary: This paper describes the systems submitted to iSarcasm shared task. The aim of iSarcasm is to identify the sarcastic contents in Arabic and English text. A multi-Layer machine learning based model has been submitted for Arabic sarcasm detection.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper describes the systems submitted to iSarcasm shared task. The aim of iSarcasm is to identify the sarcastic contents in Arabic and English text. Our team participated in iSarcasm for the Arabic language. A multi-Layer machine learning based model has been submitted for Arabic sarcasm detection. In this model, a vector space TF-IDF has been used as for feature representation. The submitted system is simple and does not need any external resources. The test results show encouraging results.

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