BFCAI at SemEval-2022 Task 6: Multi-Layer Perceptron for Sarcasm Detection in Arabic Texts
This work addresses sarcasm detection for Arabic language processing, but it is incremental as it applies a simple, existing method without external resources.
The paper tackled sarcasm detection in Arabic texts using a multi-layer perceptron with TF-IDF features, achieving encouraging results on the iSarcasm shared task.
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.