JCT at SemEval-2022 Task 6-A: Sarcasm Detection in Tweets Written in English and Arabic using Preprocessing Methods and Word N-grams
Yaakov HaCohen‐Kerner, Matan Fchima, Ilan Meyrowitsch · Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022) · 2022
In this paper, we describe our submissions to SemEval-2022 contest.We tackled subtask 6-A -"iSarcasmEval: Intended Sarcasm Detection In English and Arabic -Binary Classification".We developed different models for two languages: English and Arabic.We applied 4 supervised machine learning methods, 6 preprocessing methods for English and 3 for Arabic, and 3 oversampling methods.Our best submitted model for the English test dataset was an SVC model that balanced the dataset using SMOTE and removed stop words.For the Arabic test dataset, our best submitted model was an SVC model that preprocessed removed longation.