Abstract
In this paper, we present our system and findings for SemEval-2022 Task 6 - iSarcasmEval: Intended Sarcasm Detection in English. The main objective of this task was to identify sarcastic tweets. This task was challenging mainly due to (1) the small training dataset that contains only 3468 tweets and (2) the imbalanced class distribution (25% sarcastic and 75% non-sarcastic). Our submitted model (ranked eighth on Sub-Task A and fifth on Sub-Task C) consists of a Transformer-based approach (BERTweet model).
Cite
CITATION STYLE
Benlahbib, A., Alami, H., & Alami, A. (2022). LISACTeam at SemEval-2022 Task 6: A Transformer based Approach for Intended Sarcasm Detection in English Tweets. In SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop (pp. 993–998). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.semeval-1.139
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
