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2022 NAACL NAACL 2022

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

Abstract

AbstractThis 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.

🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio

Authors

Nsrin Ashraf , Fathy Elkazzaz , Mohamed Taha , Hamada Nayel , Tarek Elshishtawy

Topics

Machine Learning > Core Methods > Classification Machine Learning > Core Methods > Regression

Keywords

text classification sarcasm detection multilayer perceptron tf-idf vectorization
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