JUST-DEEP at SemEval-2022 Task 4: Using Deep Learning Techniques to Reveal Patronizing and Condescending Language
Mohammad Makahleh, Naba Bani Yaseen, Malak Abdullah · Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022) · 2022
Classification of language that favors or condones vulnerable communities (e.g., refugees, homeless, widows) has been considered a challenging task and a critical step in NLP applications.Moreover, the spread of this language among people and on social media harms society and harms the people concerned.Therefore, the classification of this language is considered a significant challenge for researchers in the world.In this paper, we propose JUST-DEEP architecture to classify a text and determine if it contains any form of patronizing and condescending language (Task 4-Subtask 1).The architecture uses state-of-art pre-trained models and empowers ensembling techniques that outperform the baseline (RoBERTa) in the SemEval-2022 task4 with a 0.502 F1 score.