Abstract
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.- Anthology ID:
- 2022.semeval-1.39
- Volume:
- Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
- Month:
- July
- Year:
- 2022
- Address:
- Seattle, United States
- Venue:
- SemEval
- SIGs:
- SIGLEX | SIGSEM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 308–312
- Language:
- URL:
- https://aclanthology.org/2022.semeval-1.39
- DOI:
- 10.18653/v1/2022.semeval-1.39
- Cite (ACL):
- Mohammad Makahleh, Naba Bani Yaseen, and Malak Abdullah. 2022. JUST-DEEP at SemEval-2022 Task 4: Using Deep Learning Techniques to Reveal Patronizing and Condescending Language. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 308–312, Seattle, United States. Association for Computational Linguistics.
- Cite (Informal):
- JUST-DEEP at SemEval-2022 Task 4: Using Deep Learning Techniques to Reveal Patronizing and Condescending Language (Makahleh et al., SemEval 2022)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2022.semeval-1.39.pdf