Brazilian Presidential Elections in the Era of Misinformation: A Machine Learning Approach to Analyse Fake News

  • Jairo L. Alves
  • Leila WeitzelEmail author
  • Paulo Quaresma
  • Carlos E. Cardoso
  • Luan Cunha
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11896)


As Brazil faced one of its most important elections in recent times, the fact-checking agencies handled the same kind of misinformation that has attacked voting in the US. However, stopping fake content before it goes viral remains an intense challenge. This paper examines a sample database of the 2018 Brazilian election articles shared by Brazilians over social media platforms. We evaluated three different configuration of Long Short-Term Memory. Experiment results indicate that the 3-layer Deep BiLSTMs with trainable word embeddings configuration was the best structure for fake news detection. We noticed that the developments in deep learning could potentially benefit fake news research.


Fake news Machine learning Long Short-Term Memory Word embeddings Deep learning Recurrent neural network 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Jairo L. Alves
    • 1
  • Leila Weitzel
    • 1
    Email author
  • Paulo Quaresma
    • 2
  • Carlos E. Cardoso
    • 1
  • Luan Cunha
    • 1
  1. 1.Fluminense Federal UniversityRio de JaneiroBrazil
  2. 2.Universidade de ÉvoraÉvora 17Portugal

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