@inproceedings{vazquez-ramos-etal-2022-i2c,
title = "{I}2{C} at {S}em{E}val-2022 Task 4: Patronizing and Condescending Language Detection using Deep Learning Techniques",
author = "V{\'a}zquez Ramos, Laura and
Moreno Monterde, Adri{\'a}n and
Pach{\'o}n, Victoria and
Mata, Jacinto",
editor = "Emerson, Guy and
Schluter, Natalie and
Stanovsky, Gabriel and
Kumar, Ritesh and
Palmer, Alexis and
Schneider, Nathan and
Singh, Siddharth and
Ratan, Shyam",
booktitle = "Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)",
month = jul,
year = "2022",
address = "Seattle, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.semeval-1.62",
doi = "10.18653/v1/2022.semeval-1.62",
pages = "459--463",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T I2C at SemEval-2022 Task 4: Patronizing and Condescending Language Detection using Deep Learning Techniques
%A Vázquez Ramos, Laura
%A Moreno Monterde, Adrián
%A Pachón, Victoria
%A Mata, Jacinto
%Y Emerson, Guy
%Y Schluter, Natalie
%Y Stanovsky, Gabriel
%Y Kumar, Ritesh
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y Singh, Siddharth
%Y Ratan, Shyam
%S Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, United States
%F vazquez-ramos-etal-2022-i2c
%X 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.
%R 10.18653/v1/2022.semeval-1.62
%U https://aclanthology.org/2022.semeval-1.62
%U https://doi.org/10.18653/v1/2022.semeval-1.62
%P 459-463
Markdown (Informal)
[I2C at SemEval-2022 Task 4: Patronizing and Condescending Language Detection using Deep Learning Techniques](https://aclanthology.org/2022.semeval-1.62) (Vázquez Ramos et al., SemEval 2022)
ACL