Social Network Sentiment Analysis Using Hybrid Deep Learning Models

Producción Científica

Detalles Bibliográficos
Autores: Merayo Álvarez, Noemí, Vegas Hernández, Jesús María, Llamas Bello, César, Fernández Reguero, Patricia
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:España
Institución:Universidad de Valladolid
Repositorio:UVaDOC. Repositorio Documental de la Universidad de Valladolid
OAI Identifier:oai:uvadoc.uva.es:10324/64511
Acceso en línea:https://doi.org/10.3390/app132011608
https://uvadoc.uva.es/handle/10324/64511
Access Level:acceso abierto
Palabra clave:deep learning
hybrid strategies
sentiment analysis
social networks
Twitter
Spanish
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oai_identifier_str oai:uvadoc.uva.es:10324/64511
network_acronym_str ES
network_name_str España
repository_id_str
spelling Social Network Sentiment Analysis Using Hybrid Deep Learning ModelsMerayo Álvarez, NoemíVegas Hernández, Jesús MaríaLlamas Bello, CésarFernández Reguero, Patriciadeep learninghybrid strategiessentiment analysissocial networksTwitterSpanishProducción CientíficaThe exponential growth in information on the Internet, particularly within social networks, highlights the importance of sentiment and opinion analysis. The intrinsic characteristics of the Spanish language coupled with the short length and lack of context of messages on social media pose a challenge for sentiment analysis in social networks. In this study, we present a hybrid deep learning model combining convolutional and long short-term memory layers to detect polarity levels in Twitter for the Spanish language. Our model significantly improved the accuracy of existing approaches by up to 20%, achieving accuracies of around 76% for three polarities (positive, negative, neutral) and 91% for two polarities (positive, negative).MDPI2023info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://doi.org/10.3390/app132011608https://uvadoc.uva.es/handle/10324/64511reponame:UVaDOC. Repositorio Documental de la Universidad de Valladolidinstname:Universidad de ValladolidIngléshttps://www.mdpi.com/2076-3417/13/20/11608info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/oai:uvadoc.uva.es:10324/645112026-06-13T12:44:47Z
dc.title.none.fl_str_mv Social Network Sentiment Analysis Using Hybrid Deep Learning Models
title Social Network Sentiment Analysis Using Hybrid Deep Learning Models
spellingShingle Social Network Sentiment Analysis Using Hybrid Deep Learning Models
Merayo Álvarez, Noemí
deep learning
hybrid strategies
sentiment analysis
social networks
Twitter
Spanish
title_short Social Network Sentiment Analysis Using Hybrid Deep Learning Models
title_full Social Network Sentiment Analysis Using Hybrid Deep Learning Models
title_fullStr Social Network Sentiment Analysis Using Hybrid Deep Learning Models
title_full_unstemmed Social Network Sentiment Analysis Using Hybrid Deep Learning Models
title_sort Social Network Sentiment Analysis Using Hybrid Deep Learning Models
dc.creator.none.fl_str_mv Merayo Álvarez, Noemí
Vegas Hernández, Jesús María
Llamas Bello, César
Fernández Reguero, Patricia
author Merayo Álvarez, Noemí
author_facet Merayo Álvarez, Noemí
Vegas Hernández, Jesús María
Llamas Bello, César
Fernández Reguero, Patricia
author_role author
author2 Vegas Hernández, Jesús María
Llamas Bello, César
Fernández Reguero, Patricia
author2_role author
author
author
dc.subject.none.fl_str_mv deep learning
hybrid strategies
sentiment analysis
social networks
Twitter
Spanish
topic deep learning
hybrid strategies
sentiment analysis
social networks
Twitter
Spanish
description Producción Científica
publishDate 2023
dc.date.none.fl_str_mv 2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.3390/app132011608
https://uvadoc.uva.es/handle/10324/64511
url https://doi.org/10.3390/app132011608
https://uvadoc.uva.es/handle/10324/64511
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://www.mdpi.com/2076-3417/13/20/11608
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:UVaDOC. Repositorio Documental de la Universidad de Valladolid
instname:Universidad de Valladolid
instname_str Universidad de Valladolid
reponame_str UVaDOC. Repositorio Documental de la Universidad de Valladolid
collection UVaDOC. Repositorio Documental de la Universidad de Valladolid
repository.name.fl_str_mv
repository.mail.fl_str_mv
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