FII UAIC at SemEval-2022 Task 6: iSarcasmEval - Intended Sarcasm Detection in English and Arabic

Tudor Manoleasa, Daniela Gifu, Iustin Sandu


Abstract
The “iSarcasmEval - Intended Sarcasm Detection in English and Arabic” task at the SemEval 2022 competition focuses on detectingand rating the distinction between intendedand perceived sarcasm in the context of textual sarcasm detection, as well as the level ofirony contained in these texts. In the contextof SemEval, we present a binary classificationmethod which classifies the text as sarcasticor non-sarcastic (task A, for English) based onfive classical machine learning approaches bytrying to train the models based on this datasetsolely (i.e., no other datasets have been used).This process indicates low performance compared to previously studied datasets, which in2dicates that the previous ones might be biased.
Anthology ID:
2022.semeval-1.136
Volume:
Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
Month:
July
Year:
2022
Address:
Seattle, United States
Editors:
Guy Emerson, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh, Shyam Ratan
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
970–977
Language:
URL:
https://aclanthology.org/2022.semeval-1.136
DOI:
10.18653/v1/2022.semeval-1.136
Bibkey:
Cite (ACL):
Tudor Manoleasa, Daniela Gifu, and Iustin Sandu. 2022. FII UAIC at SemEval-2022 Task 6: iSarcasmEval - Intended Sarcasm Detection in English and Arabic. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 970–977, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
FII UAIC at SemEval-2022 Task 6: iSarcasmEval - Intended Sarcasm Detection in English and Arabic (Manoleasa et al., SemEval 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.semeval-1.136.pdf
Data
iSarcasmEval