A Language Model for Misogyny Detection in Latin American Spanish Driven by Multisource Feature Extraction and Transformers

Creating effective mechanisms to detect misogyny online automatically represents significant scientific and technological challenges. The complexity of recognizing misogyny through computer models lies in the fact that it is a subtle type of violence, it is not always explicitly aggressive, and it c...

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Autores principales:	Edwin Aldana-Bobadilla, Alejandro Molina-Villegas, Yuridia Montelongo-Padilla, Ivan Lopez-Arevalo, Oscar S. Sordia
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	automatic hate speech detection multisource feature extraction Latin American Spanish language models natural language processing Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/54ae1574c93c4cd9929ecf4c8953edae
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id	oai:doaj.org-article:54ae1574c93c4cd9929ecf4c8953edae
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spelling	oai:doaj.org-article:54ae1574c93c4cd9929ecf4c8953edae2021-11-11T15:24:42ZA Language Model for Misogyny Detection in Latin American Spanish Driven by Multisource Feature Extraction and Transformers10.3390/app1121104672076-3417https://doaj.org/article/54ae1574c93c4cd9929ecf4c8953edae2021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/10467https://doaj.org/toc/2076-3417Creating effective mechanisms to detect misogyny online automatically represents significant scientific and technological challenges. The complexity of recognizing misogyny through computer models lies in the fact that it is a subtle type of violence, it is not always explicitly aggressive, and it can even hide behind seemingly flattering words, jokes, parodies, and other expressions. Currently, it is even difficult to have an exact figure for the rate of misogynistic comments online because, unlike other types of violence, such as physical violence, these events are not registered by any statistical systems. This research contributes to the development of models for the automatic detection of misogynistic texts in Latin American Spanish and contributes to the design of data augmentation methodologies since the amount of data required for deep learning models is considerable.Edwin Aldana-BobadillaAlejandro Molina-VillegasYuridia Montelongo-PadillaIvan Lopez-ArevaloOscar S. SordiaMDPI AGarticleautomatic hate speech detectionmultisource feature extractionLatin American Spanish language modelsnatural language processingTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10467, p 10467 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	automatic hate speech detection multisource feature extraction Latin American Spanish language models natural language processing Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	automatic hate speech detection multisource feature extraction Latin American Spanish language models natural language processing Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Edwin Aldana-Bobadilla Alejandro Molina-Villegas Yuridia Montelongo-Padilla Ivan Lopez-Arevalo Oscar S. Sordia A Language Model for Misogyny Detection in Latin American Spanish Driven by Multisource Feature Extraction and Transformers
description	Creating effective mechanisms to detect misogyny online automatically represents significant scientific and technological challenges. The complexity of recognizing misogyny through computer models lies in the fact that it is a subtle type of violence, it is not always explicitly aggressive, and it can even hide behind seemingly flattering words, jokes, parodies, and other expressions. Currently, it is even difficult to have an exact figure for the rate of misogynistic comments online because, unlike other types of violence, such as physical violence, these events are not registered by any statistical systems. This research contributes to the development of models for the automatic detection of misogynistic texts in Latin American Spanish and contributes to the design of data augmentation methodologies since the amount of data required for deep learning models is considerable.
format	article
author	Edwin Aldana-Bobadilla Alejandro Molina-Villegas Yuridia Montelongo-Padilla Ivan Lopez-Arevalo Oscar S. Sordia
author_facet	Edwin Aldana-Bobadilla Alejandro Molina-Villegas Yuridia Montelongo-Padilla Ivan Lopez-Arevalo Oscar S. Sordia
author_sort	Edwin Aldana-Bobadilla
title	A Language Model for Misogyny Detection in Latin American Spanish Driven by Multisource Feature Extraction and Transformers
title_short	A Language Model for Misogyny Detection in Latin American Spanish Driven by Multisource Feature Extraction and Transformers
title_full	A Language Model for Misogyny Detection in Latin American Spanish Driven by Multisource Feature Extraction and Transformers
title_fullStr	A Language Model for Misogyny Detection in Latin American Spanish Driven by Multisource Feature Extraction and Transformers
title_full_unstemmed	A Language Model for Misogyny Detection in Latin American Spanish Driven by Multisource Feature Extraction and Transformers
title_sort	language model for misogyny detection in latin american spanish driven by multisource feature extraction and transformers
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/54ae1574c93c4cd9929ecf4c8953edae
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A Language Model for Misogyny Detection in Latin American Spanish Driven by Multisource Feature Extraction and Transformers

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