MN-DS: A Multilabeled News Dataset for News Articles Hierarchical Classification

Alina Petukhova; Nuno Fachada

doi:10.3390/data8050074

MN-DS: A Multilabeled News Dataset for News Articles Hierarchical Classification

Alina Petukhova, Nuno Fachada

Resultado de pesquisa

9 Citações (Scopus)

6 Transferências (Pure)

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

Idioma original	Inglês
Número do artigo	74
Revista	Data
Volume	8
Número de emissão	5
DOIs	https://doi.org/10.3390/data8050074
Estado da publicação	Publicadas - 23 abr. 2023

Keywords

RECOLHA DE DADOS
NOTÍCIAS
PROCESSAMENTO DA LINGUAGEM NATURAL
COMUNICAÇÃO SOCIAL
PROCESSAMENTO DE DADOS
TAXONOMIA
INFORMÁTICA

Acesso ao documento

10.3390/data8050074

2023 data mnds???researchoutput.electronicversion.versiontype.publishersversion???, 1,17 MB

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MN-DS: A Multilabeled News Dataset for News Articles Hierarchical Classification

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