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2022 SEMEVAL SemEval 2022

LISACTeam at SemEval-2022 Task 6: A Transformer based Approach for Intended Sarcasm Detection in English Tweets

Abstract

AbstractIn 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).

🌉 Interdisciplinary Bridge — Deep Learning and Interdisciplinary and Natural Language Processing
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio

Authors

Abdessamad Benlahbib , Hamza Alami , Ahmed Alami

Topics

Deep Learning > Architectures > Transformers Natural Language Processing > Understanding > Sentiment Analysis Natural Language Processing > Applications > Text Classification Interdisciplinary > Social > Social Media Analysis

Keywords

text classification sarcasm detection class imbalance transformer model intended sarcasm
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