Abstract
This paper describes our submissions to SemEval-2022 subtask 4-A - 'Patronizing and Condescending Language Detection: Binary Classification". We developed different models for this subtask. We applied 11 supervised machine learning methods and 9 preprocessing methods. Our best submission was a model we built with BertForSequenceClassification. Our experiments indicate that pre-processing stage is a must for a successful model. The dataset for Subtask 1 is highly imbalanced. The F1-scores on the oversampled imbalanced training dataset were higher than the results on the original training dataset.
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
Cite
CITATION STYLE
HaCohen-Kerner, Y., Meyrowitsch, I., & Fchima, M. (2022). JCT at SemEval-2022 Task 4-A: Patronism Detection in Posts Written in English using Pre-processing Methods and various Machine Learning Methods. In SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop (pp. 519–524). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.semeval-1.72
Readers over time
Readers' Seniority
Readers' Discipline
