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 that 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.
CITATION STYLE
Xu, J. (2022). Xu at SemEval-2022 Task 4: Pre-BERT Neural Network Methods vs Post-BERT RoBERTa Approach for Patronizing and Condescending Language Detection. In SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop (pp. 479–484). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.semeval-1.65
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