MN-DS: A Multilabeled News Dataset for News Articles Hierarchical Classification
Autor(a) principal: | |
---|---|
Data de Publicação: | 2023 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://doi.org/10.3390/data8050074 http://hdl.handle.net/10437/13813 |
Resumo: | This article presents a dataset of 10,917 news articles with hierarchical news categories collected between 1 January 2019 and 31 December 2019. We manually labeled the articles based on a hierarchical taxonomy with 17 first-level and 109 second-level categories. This dataset can be used to train machine learning models for automatically classifying news articles by topic. This dataset can be helpful for researchers working on news structuring, classification, and predicting future events based on released news. Keywords: news dataset; text classification; NLP; media topic taxonomy |
id |
RCAP_dcb6379e13ee6cc7562e456d0c5ebe0e |
---|---|
oai_identifier_str |
oai:recil.ensinolusofona.pt:10437/13813 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
MN-DS: A Multilabeled News Dataset for News Articles Hierarchical ClassificationRECOLHA DE DADOSNOTÍCIASPROCESSAMENTO DA LINGUAGEM NATURALCOMUNICAÇÃO SOCIALPROCESSAMENTO DE DADOSTAXONOMIAINFORMÁTICADATA COLLECTIONNEWSNATURAL LANGUAGE PROCESSINGMEDIADATA PROCESSINGTAXONOMYCOMPUTER SCIENCEThis article presents a dataset of 10,917 news articles with hierarchical news categories collected between 1 January 2019 and 31 December 2019. We manually labeled the articles based on a hierarchical taxonomy with 17 first-level and 109 second-level categories. This dataset can be used to train machine learning models for automatically classifying news articles by topic. This dataset can be helpful for researchers working on news structuring, classification, and predicting future events based on released news. Keywords: news dataset; text classification; NLP; media topic taxonomyMDPI2023-04-28T12:14:12Z2023-04-23T00:00:00Z2023-04-23info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://doi.org/10.3390/data8050074http://hdl.handle.net/10437/13813eng2306-5729Petukhova, AlinaFachada, Nunoinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-05T01:30:52Zoai:recil.ensinolusofona.pt:10437/13813Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:50:54.394656Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
MN-DS: A Multilabeled News Dataset for News Articles Hierarchical Classification |
title |
MN-DS: A Multilabeled News Dataset for News Articles Hierarchical Classification |
spellingShingle |
MN-DS: A Multilabeled News Dataset for News Articles Hierarchical Classification Petukhova, Alina RECOLHA DE DADOS NOTÍCIAS PROCESSAMENTO DA LINGUAGEM NATURAL COMUNICAÇÃO SOCIAL PROCESSAMENTO DE DADOS TAXONOMIA INFORMÁTICA DATA COLLECTION NEWS NATURAL LANGUAGE PROCESSING MEDIA DATA PROCESSING TAXONOMY COMPUTER SCIENCE |
title_short |
MN-DS: A Multilabeled News Dataset for News Articles Hierarchical Classification |
title_full |
MN-DS: A Multilabeled News Dataset for News Articles Hierarchical Classification |
title_fullStr |
MN-DS: A Multilabeled News Dataset for News Articles Hierarchical Classification |
title_full_unstemmed |
MN-DS: A Multilabeled News Dataset for News Articles Hierarchical Classification |
title_sort |
MN-DS: A Multilabeled News Dataset for News Articles Hierarchical Classification |
author |
Petukhova, Alina |
author_facet |
Petukhova, Alina Fachada, Nuno |
author_role |
author |
author2 |
Fachada, Nuno |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Petukhova, Alina Fachada, Nuno |
dc.subject.por.fl_str_mv |
RECOLHA DE DADOS NOTÍCIAS PROCESSAMENTO DA LINGUAGEM NATURAL COMUNICAÇÃO SOCIAL PROCESSAMENTO DE DADOS TAXONOMIA INFORMÁTICA DATA COLLECTION NEWS NATURAL LANGUAGE PROCESSING MEDIA DATA PROCESSING TAXONOMY COMPUTER SCIENCE |
topic |
RECOLHA DE DADOS NOTÍCIAS PROCESSAMENTO DA LINGUAGEM NATURAL COMUNICAÇÃO SOCIAL PROCESSAMENTO DE DADOS TAXONOMIA INFORMÁTICA DATA COLLECTION NEWS NATURAL LANGUAGE PROCESSING MEDIA DATA PROCESSING TAXONOMY COMPUTER SCIENCE |
description |
This article presents a dataset of 10,917 news articles with hierarchical news categories collected between 1 January 2019 and 31 December 2019. We manually labeled the articles based on a hierarchical taxonomy with 17 first-level and 109 second-level categories. This dataset can be used to train machine learning models for automatically classifying news articles by topic. This dataset can be helpful for researchers working on news structuring, classification, and predicting future events based on released news. Keywords: news dataset; text classification; NLP; media topic taxonomy |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-04-28T12:14:12Z 2023-04-23T00:00:00Z 2023-04-23 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://doi.org/10.3390/data8050074 http://hdl.handle.net/10437/13813 |
url |
https://doi.org/10.3390/data8050074 http://hdl.handle.net/10437/13813 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2306-5729 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799131587669917696 |