TUG-CIC at SemEval-2021 Task 6: Two-stage Fine-tuning for Intended Sarcasm Detection

Jason Angel, Segun Aroyehun, Alexander Gelbukh


Abstract
We present our systems and findings for the iSarcasmEval: Intended Sarcasm Detection In English and Arabic at SEMEVAL 2022. Specifically we take part in Subtask A for the English language. The task aims to determine whether a text from social media (a tweet) is sarcastic or not. We model the problem using knowledge sources, a pre-trained language model on sentiment/emotion data and a dataset focused on intended sarcasm. Our submission ranked third place among 43 teams. In addition, we show a brief error analysis of our best model to investigate challenging examples for detecting sarcasm.
Anthology ID:
2022.semeval-1.133
Volume:
Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
Month:
July
Year:
2022
Address:
Seattle, United States
Venue:
SemEval
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
951–955
Language:
URL:
https://aclanthology.org/2022.semeval-1.133
DOI:
10.18653/v1/2022.semeval-1.133
Bibkey:
Cite (ACL):
Jason Angel, Segun Aroyehun, and Alexander Gelbukh. 2022. TUG-CIC at SemEval-2021 Task 6: Two-stage Fine-tuning for Intended Sarcasm Detection. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 951–955, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
TUG-CIC at SemEval-2021 Task 6: Two-stage Fine-tuning for Intended Sarcasm Detection (Angel et al., SemEval 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.semeval-1.133.pdf
Data
SPIRSiSarcasmEval