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recogna-nlp/fakerecogna2-abstrativa

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Permissive or share-alike

The declared licence (mit) is classified as permissive.

Declared licence: mit, from the tagEvidence: README.md at 0247b2e
Licence files: No licence file at the top level of the repositoryEvidence: file list at 0247b2e
Declared sources: None listed in the card metadata
Access gated on Hugging Face: No

Each cell links to what was checked: a file, a file list or a Hub record.

Tasks

text-classification

Citation text from the card

@inproceedings{garcia-etal-2024-text,
    title = "Text Summarization and Temporal Learning Models Applied to {P}ortuguese Fake News Detection in a Novel {B}razilian Corpus Dataset",
    author = "Garcia, Gabriel Lino  and
      Paiola, Pedro Henrique  and
      Jodas, Danilo Samuel  and
      Sugi, Luis Afonso  and
      Papa, Jo{\~a}o Paulo",
    editor = "Gamallo, Pablo  and
      Claro, Daniela  and
      Teixeira, Ant{\'o}nio  and
      Real, Livy  and
      Garcia, Marcos  and
      Oliveira, Hugo Gon{\c{c}}alo  and
      Amaro, Raquel",
    booktitle = "Proceedings of the 16th International Conference on Computational Processing of Portuguese - Vol. 1",
    month = mar,
    year = "2024",
    address = "Santiago de Compostela, Galicia/Spain",
    publisher = "Association for Computational Lingustics",
    url = "https://aclanthology.org/2024.propor-1.9/",
    pages = "86--96"
    }

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dataset_licence({ "id": "recogna-nlp/fakerecogna2-abstrativa" })
signal: "permissive"
stated_licence: "mit"
sources: 0