I2C at SemEval-2022 Task 4: Patronizing and Condescending Language Detection using Deep Learning Techniques

Laura Vázquez Ramos, Adrián Moreno Monterde, Victoria Pachón, Jacinto Mata


Abstract
Patronizing and Condescending Language is an ever-present problem in our day-to-day lives. There has been a rise in patronizing language on social media platforms manifesting itself in various forms. This paper presents two performing deep learning algorithms and results for the “Task 4: Patronizing and Condescending Language Detection.” of SemEval 2022. The task incorporates an English dataset containing sentences from social media from around the world. The paper focuses on data augmentation to boost results on various deep learning methods as BERT and LSTM Neural Network.
Anthology ID:
2022.semeval-1.62
Volume:
Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
Month:
July
Year:
2022
Address:
Seattle, United States
Editors:
Guy Emerson, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh, Shyam Ratan
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
459–463
Language:
URL:
https://aclanthology.org/2022.semeval-1.62
DOI:
10.18653/v1/2022.semeval-1.62
Bibkey:
Cite (ACL):
Laura Vázquez Ramos, Adrián Moreno Monterde, Victoria Pachón, and Jacinto Mata. 2022. I2C at SemEval-2022 Task 4: Patronizing and Condescending Language Detection using Deep Learning Techniques. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 459–463, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
I2C at SemEval-2022 Task 4: Patronizing and Condescending Language Detection using Deep Learning Techniques (Vázquez Ramos et al., SemEval 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.semeval-1.62.pdf