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

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

From MaRDI portal



DOI10.5281/zenodo.7394851Zenodo7394851MaRDI QIDQ6676388

Dataset published at Zenodo repository.

Author name not available (Why is that?)

Publication date: 3 December 2022

Copyright license: No records found.



Description

Overview This dataset contains 10,917 news articles with hierarchical news categories collected between January 1st 2019, and December 31st 2019 classified by using NewsCodes Media Topic taxonomy. We manually labelled 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. Reproducibility of results The results presented in the research paper MN-DS: A Multilabeled News Dataset for News Articles Hierarchical Classification, technical validation can be reproduced using functions in github repository. Licenses The dataset is made available under a CC-BY 4.0 license (see `LICENSE_DATA.txt`).






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