Detection of Misinformation about COVID-19 in Brazilian Portuguese WhatsApp Messages Using Deep Learning

  • Antônio Diogo Forte Martins Universidade Federal do Ceará (UFC)
  • Lucas Cabral Universidade Federal do Ceará (UFC)
  • Pedro Jorge Chaves Mourão Universidade Estadual do Ceará (UECE)
  • José Maria Monteiro Universidade Federal do Ceará (UFC)
  • Javam Machado Universidade Federal do Ceará (UFC)


During the COVID-19 pandemic, the misinformation problem arose once again through social networks, like a harmful health advice and false solutions epidemic. In Brazil, as well as in many developing countries, one of the primary sources of misinformation is the messaging application WhatsApp. Thus, the automatic misinformation detection (MID) about COVID-19 in Brazilian Portuguese WhatsApp messages becomes a crucial challenge. Still, due to WhatsApp's private messaging nature, there are still few methods of misinformation detection developed specifically for the WhatsApp platform. In this paper, we propose a new approach, called MIDeepBR, based on BiLSTM neural networks, pooling operations and attention mechanism, which is able to automatically detect misinformation in Brazilian Portuguese WhatsApp messages. Experimental results evidence the suitability of the proposed approach to automatic misinformation detection. Our best results achieved an F1 score of 0.834, while in previous works, the best results achieved an F1 score of 0.778. Thus, MIDeepBR outperforms the previous works.
Palavras-chave: COVID19, Coronavirus, Misinformation, Whatsapp


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MARTINS, Antônio Diogo Forte; CABRAL, Lucas; MOURÃO, Pedro Jorge Chaves; MONTEIRO, José Maria; MACHADO, Javam. Detection of Misinformation about COVID-19 in Brazilian Portuguese WhatsApp Messages Using Deep Learning. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 36. , 2021, Rio de Janeiro. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 85-96. ISSN 2763-8979. DOI: