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.
Cite
CITATION STYLE
Ashraf, N., Elkazaz, F., Taha, M., Nayel, H., & Elshishtawy, T. (2022). BFCAI at SemEval-2022 Task 6: Multi-Layer Perceptron for Sarcasm Detection in Arabic Texts. In SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop (pp. 881–884). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.semeval-1.123
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
