Fake News Detection about Covid-19 in the Portuguese Language

  • Anísio Pereira Batista Filho UNIVASF
  • Débora da Conceição Araújo UNIVASF / UFPE
  • Máverick André Dionísio Ferreira UFPE
  • Paulo Salgado Gomes de Mattos Neto UFPE


A disseminação de notícias falsas tem sido um problema notado em diversos setores da sociedade, e vem dificultando o combate à pandemia causada pelo novo coronavírus (Sars-Cov-2). Combater desinformação sobre o Sars-Cov-2, principalmente nas redes sociais, é de fundamental importância para o controle da propagação do vírus e, consequentemente, da pandemia. Diante disso, nesse trabalho são construídos modelos de aprendizado supervisionado focados na identificação de notícias falsas sobre o novo coronavírus. Como resultados, foram construídos e avaliados 18 modelos, os quais chegaram a alcançar 0.62%, 0.82% e 0.47% de f-score para as classes consideradas (news, opinion e fake).


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BATISTA FILHO, Anísio Pereira; ARAÚJO, Débora da Conceição; FERREIRA, Máverick André Dionísio; MATTOS NETO, Paulo Salgado Gomes de. Fake News Detection about Covid-19 in the Portuguese Language. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 18. , 2021, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 492-503. DOI: https://doi.org/10.5753/eniac.2021.18278.

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