Amrita_CEN at SemEval-2022 Task 6: A Machine Learning Approach for Detecting Intended Sarcasm using Oversampling
Aparna K Ajayan, Krishna Mohanan, Anugraha S, Premjith B, Soman Kp
Abstract
This paper describes the submission of the team Amrita_CEN to the shared task on iSarcasm Eval: Intended Sarcasm Detection in English and Arabic at SemEval 2022. We employed machine learning algorithms towards sarcasm detection. Here, we used K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Naïve Bayes, Logistic Regression, and Decision Tree along with the Random Forest ensemble method. Additionally, feature engineering techniques were applied to deal with the problems of class imbalance during training. Among the models considered, our study shows that the SVM, logistic regression and ensemble model Random Forest exhibited the best performance, which was submitted to the shared task.- Anthology ID:
- 2022.semeval-1.115
- 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:
- 834–839
- Language:
- URL:
- https://aclanthology.org/2022.semeval-1.115
- DOI:
- 10.18653/v1/2022.semeval-1.115
- Cite (ACL):
- Aparna K Ajayan, Krishna Mohanan, Anugraha S, Premjith B, and Soman Kp. 2022. Amrita_CEN at SemEval-2022 Task 6: A Machine Learning Approach for Detecting Intended Sarcasm using Oversampling. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 834–839, Seattle, United States. Association for Computational Linguistics.
- Cite (Informal):
- Amrita_CEN at SemEval-2022 Task 6: A Machine Learning Approach for Detecting Intended Sarcasm using Oversampling (K Ajayan et al., SemEval 2022)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2022.semeval-1.115.pdf
- Data
- iSarcasm