A Spanish dataset for Targeted Sentiment Analysis of political headlines

Autores
Alves Salgueiro, Tomás; Recart Zapata, Emilio; Furman, Damián; Pérez, Juan Manuel; Fernández Larrosa, Pablo Nicolás
Año de publicación
2022
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Subjective texts have been especially studied by several works as they can induce certain behaviours in their users. Most work focuses on user-generated texts in social networks, but some other texts also comprise opinions on  certain topics and could influence judgement criteria during political decisions. In this work, we address the task of Targeted Sentiment Analysis for the domain of news headlines, published by the main outlets during the 2019 Argentinean Presidential Elections. For this purpose, we present a polarity dataset of 1,976 headlines mentioning candidates in the 2019 elections at the target level. Preliminary experiments with state-of-the-art classification algorithms based on pre-trained linguistic models suggest that target information is helpful for this task. We make our data and pre-trained models publicly available.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Targeted Sentiment Analysis
polarity dataset
linguistic models
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/151701
Acceder
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repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling A Spanish dataset for Targeted Sentiment Analysis of political headlinesAlves Salgueiro, TomásRecart Zapata, EmilioFurman, DamiánPérez, Juan ManuelFernández Larrosa, Pablo NicolásCiencias InformáticasTargeted Sentiment Analysispolarity datasetlinguistic modelsSubjective texts have been especially studied by several works as they can induce certain behaviours in their users. Most work focuses on user-generated texts in social networks, but some other texts also comprise opinions on  certain topics and could influence judgement criteria during political decisions. In this work, we address the task of Targeted Sentiment Analysis for the domain of news headlines, published by the main outlets during the 2019 Argentinean Presidential Elections. For this purpose, we present a polarity dataset of 1,976 headlines mentioning candidates in the 2019 elections at the target level. Preliminary experiments with state-of-the-art classification algorithms based on pre-trained linguistic models suggest that target information is helpful for this task. We make our data and pre-trained models publicly available.Sociedad Argentina de Informática e Investigación Operativa2022-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf92-97http://sedici.unlp.edu.ar/handle/10915/151701enginfo:eu-repo/semantics/altIdentifier/url/https://publicaciones.sadio.org.ar/index.php/JAIIO/article/download/269/220info:eu-repo/semantics/altIdentifier/issn/2451-7496info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T11:11:05Zoai:sedici.unlp.edu.ar:10915/151701Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 11:11:05.776SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv A Spanish dataset for Targeted Sentiment Analysis of political headlines
title A Spanish dataset for Targeted Sentiment Analysis of political headlines
spellingShingle A Spanish dataset for Targeted Sentiment Analysis of political headlines
Alves Salgueiro, Tomás
Ciencias Informáticas
Targeted Sentiment Analysis
polarity dataset
linguistic models
title_short A Spanish dataset for Targeted Sentiment Analysis of political headlines
title_full A Spanish dataset for Targeted Sentiment Analysis of political headlines
title_fullStr A Spanish dataset for Targeted Sentiment Analysis of political headlines
title_full_unstemmed A Spanish dataset for Targeted Sentiment Analysis of political headlines
title_sort A Spanish dataset for Targeted Sentiment Analysis of political headlines
dc.creator.none.fl_str_mv Alves Salgueiro, Tomás
Recart Zapata, Emilio
Furman, Damián
Pérez, Juan Manuel
Fernández Larrosa, Pablo Nicolás
author Alves Salgueiro, Tomás
author_facet Alves Salgueiro, Tomás
Recart Zapata, Emilio
Furman, Damián
Pérez, Juan Manuel
Fernández Larrosa, Pablo Nicolás
author_role author
author2 Recart Zapata, Emilio
Furman, Damián
Pérez, Juan Manuel
Fernández Larrosa, Pablo Nicolás
author2_role author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Targeted Sentiment Analysis
polarity dataset
linguistic models
topic Ciencias Informáticas
Targeted Sentiment Analysis
polarity dataset
linguistic models
dc.description.none.fl_txt_mv Subjective texts have been especially studied by several works as they can induce certain behaviours in their users. Most work focuses on user-generated texts in social networks, but some other texts also comprise opinions on  certain topics and could influence judgement criteria during political decisions. In this work, we address the task of Targeted Sentiment Analysis for the domain of news headlines, published by the main outlets during the 2019 Argentinean Presidential Elections. For this purpose, we present a polarity dataset of 1,976 headlines mentioning candidates in the 2019 elections at the target level. Preliminary experiments with state-of-the-art classification algorithms based on pre-trained linguistic models suggest that target information is helpful for this task. We make our data and pre-trained models publicly available.
Sociedad Argentina de Informática e Investigación Operativa
description Subjective texts have been especially studied by several works as they can induce certain behaviours in their users. Most work focuses on user-generated texts in social networks, but some other texts also comprise opinions on  certain topics and could influence judgement criteria during political decisions. In this work, we address the task of Targeted Sentiment Analysis for the domain of news headlines, published by the main outlets during the 2019 Argentinean Presidential Elections. For this purpose, we present a polarity dataset of 1,976 headlines mentioning candidates in the 2019 elections at the target level. Preliminary experiments with state-of-the-art classification algorithms based on pre-trained linguistic models suggest that target information is helpful for this task. We make our data and pre-trained models publicly available.
publishDate 2022
dc.date.none.fl_str_mv 2022-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/151701
url http://sedici.unlp.edu.ar/handle/10915/151701
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://publicaciones.sadio.org.ar/index.php/JAIIO/article/download/269/220
info:eu-repo/semantics/altIdentifier/issn/2451-7496
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
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collection SEDICI (UNLP)
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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score 13.13397

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