The 'iSarcasmEval - Intended Sarcasm Detection in English and Arabic' task at the SemEval 2022 competition focuses on detecting and rating the distinction between intended and perceived sarcasm in the context of textual sarcasm detection, as well as the level of irony contained in these texts. In the context of SemEval, we present a binary classification method which classifies the text as sarcastic or non-sarcastic (task A, for English) based on five classical machine learning approaches by trying to train the models based on this dataset solely (i.e., no other datasets have been used). This process indicates low performance compared to previously studied datasets, which indicates that the previous ones might be biased.
CITATION STYLE
Manoleasa, T., Sandu, I., Gifu, D., & Trandabat, D. (2022). FII UAIC at SemEval-2022 Task 6: iSarcasmEval - Intended Sarcasm Detection in English and Arabic. In SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop (pp. 970–977). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.semeval-1.136
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