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Xu at SemEval-2022 Task 4: Pre-BERT Neural Network Methods vs Post-BERT RoBERTa Approach for Patronizing and Condescending Language Detection

2022-11-13 10:59:45
Jinghua Xu
arXiv_CL
       
Abstract

This paper describes my participation in the SemEval-2022 Task 4: Patronizing and Condescending Language Detection. I participate in both subtasks: Patronizing and Condescending Language (PCL) Identification and Patronizing and Condescending Language Categorization, with the main focus put on subtask 1. The experiments compare pre-BERT neural network (NN) based systems against post-BERT pretrained language model RoBERTa. This research finds NN-based systems in the experiments perform worse on the task compared to the pretrained language models. The top-performing RoBERTa system is ranked 26 out of 78 teams (F1-score: 54.64) in subtask 1, and 23 out of 49 teams (F1-score: 30.03) in subtask 2.

Abstract (translated)

URL

https://arxiv.org/abs/2211.06874

PDF

https://arxiv.org/pdf/2211.06874.pdf

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