Automatic Misogyny Detection in Social Media: A Survey
Título del documento: Automatic Misogyny Detection in Social Media: A Survey
Revista: Computación y Sistemas
Base de datos: PERIÓDICA
Número de sistema: 000456944
ISSN: 1405-5546
Autors: 1
1
Institucions: 1Technological University, Dublín. Irlanda
Any:
Període: Oct-Dic
Volum: 23
Número: 4
Paginació: 1159-1164
País: México
Idioma: Inglés
Tipo de documento: Artículo
Enfoque: Aplicado, descriptivo
Resumen en inglés This article presents a survey of automated misogyny identification techniques in social media, especially in Twitter. This problem is urgent because of the high speed at which messages on social platforms grow and the widespread use of offensive language (including misogynistic language) in them. In this article we survey approaches proposed in the literature to solve the problem of misogynistic message recognition. These include classical machine learning models like Support Vector Machines, Naive Bayes, Logistic Regression and ensembles of different classical machine learning models, as well as deep neural networks such as Long Short-term memory and Convolutional Neural Networks. We consider results of experiments with these models in different languages: English, Spanish and Italian tweets. The survey describes some features, which help to identify misogynistic tweets and some challenges, which aim was to create misogyny language classifiers. The survey includes not only models, which help to identify misogyny language, but also systems which help to recognize a target of an offense (an individual or a group of persons)
Disciplines Ciencias de la computación
Paraules clau: Inteligencia artificial,
Procesamiento de datos,
Programación,
Redes,
Twitter,
Detección automática,
Misoginia,
Aprendizaje automático,
Redes neuronales
Keyword: Artificial intelligence,
Data processing,
Programming,
Networks,
Twitter,
Automatic detection,
Misogyny,
Machine learning,
Deep neural networks
Text complet: Texto completo (Ver HTML) Texto completo (Ver PDF)