Awesome

Fake.Br Corpus

Hello! Thank you for using our corpus!

Here you may find 3 folders, with two of them containing versions of the same corpus:

• full_texts folder, which contains the full texts, as collected from their websites. Inside this folder, there are 4 more folders:

  • fake folder: it contains the collected fake news;
  • true folder: it contains the collected true news;
  • fake-meta-information folder: it contains the metadata information of each fake news;
  • true-meta-information folder: it contains the metadata information of each true news;

  The files in the fake and true metadata information folders follow the following model (line by line):

   author
   link
   category
   date of publication
   number of tokens
   number of words without punctuation
   number of types
   number of links inside the news
   number of words in upper case
   number of verbs
   number of subjuntive and imperative verbs
   number of nouns
   number of adjectives
   number of adverbs
   number of modal verbs (mainly auxiliary verbs)
   number of singular first and second personal pronouns
   number of plural first personal pronouns
   number of pronouns
   pausality
   number of characters
   average sentence length
   average word length
   percentage of news with speeling errors
   emotiveness
   diversity
  

  To find the aligned true and fake news pairs is very simple, as they are equally numbered/named inside their folders.

• size_normalized_texts folder, which contains the truncated texts, where, in each fake-true pair, the longer text is truncated (in number of words) to the size of the shorter text. This version of the corpus may be useful for avoiding bias in machine learning experiments.

• preprocessed folder, which contains a CSV file containing news label and pre-processed news text, such as removed portuguese stopwords, accent and diacritic (text normalization, contribution by @GuilhermeZaniniMoreira)

Finally, if you use our corpus, please include a citation to our project website and the corresponding paper published in PROPOR 2018 conference:

Monteiro R.A., Santos R.L.S., Pardo T.A.S., de Almeida T.A., Ruiz E.E.S., Vale O.A. (2018) Contributions to the Study of Fake News in Portuguese: New Corpus and Automatic Detection Results. In: Villavicencio A. et al. (eds) Computational Processing of the Portuguese Language. PROPOR 2018. Lecture Notes in Computer Science, vol 11122. Springer, Cham

or our paper published in Expert Systems with Applications:

Silva, Renato M., Santos R.L.S, Almeida T.A, and Pardo T.A.S. (2020) "Towards Automatically Filtering Fake News in Portuguese." Expert Systems with Applications, vol 146, p. 113199.

Bibtex:

@InProceedings{fakebr:18,
author={Monteiro, Rafael A. and Santos, Roney L. S. and Pardo, Thiago A. S. and de Almeida, Tiago A. and Ruiz, Evandro E. S. and Vale, Oto A.},
title={Contributions to the Study of Fake News in Portuguese: New Corpus and Automatic Detection Results},
booktitle={Computational Processing of the Portuguese Language},
year={2018},
publisher={Springer International Publishing},
pages={324--334},
isbn={978-3-319-99722-3},
}

@article{silva:20,
title = "Towards automatically filtering fake news in Portuguese",
journal = "Expert Systems with Applications",
volume = "146",
pages = "113199",
year = "2020",
issn = "0957-4174",
doi = "https://doi.org/10.1016/j.eswa.2020.113199",
url = "http://www.sciencedirect.com/science/article/pii/S0957417420300257",
author = "Renato M. Silva and Roney L.S. Santos and Tiago A. Almeida and Thiago A.S. Pardo",
}