Work

JCT at SemEval-2022 Task 4-A: Patronism Detection in Posts Written in English using Preprocessing Methods and various Machine Leaerning Methods

Year: 2022

Type: conference-paper

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.

Source: International Workshop on Semantic Evaluation (SemEval)

DOI: 10.18653/v1/2022.semeval-1.72

Authors: Yaakov HaCohen-Kerner, Ilan Meyrowitsch, Matan Fchima

Language: English

Topic: Hate Speech and Cyberbullying Detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4287889453

FWCI:

Cites: 25

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Related to: 10