A Sentiment-Based Multimodal Method to Detect Fake News

  • Igor Maffei Libonati Maia IME
  • Marcelo Pereira de Souza IME
  • Flávio Roberto Matias da Silva IME
  • Paulo Márcio Souza Freire IME
  • Ronaldo Ribeiro Goldschmidt IME

Resumo


The dissemination of news through digital media has amplified Fake News proliferation. In the face of this scenario, sentiment-based methods have presented promising results in Fake News detection. Although sentiment-based methods can extract sentiment (i.e., polarity and/or emotion) from either texts or images available in news, the ones applied to Portuguese-written news have considered sentiment exclusively extracted from texts. Thus, this study proposes a multimodal method that, besides the polarity and emotions extracted from texts, also considers sentiment extracted from news' images in order to detect Fake News written in Portuguese. The proposed method showed promising results in experimental data, overcoming the baseline methods in 8 p.p.
Palavras-chave: Fake News Detection, Machine Learning, Natural Language Processing, Sentiment Analysis, Multimodal
Publicado
05/11/2021
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MAIA, Igor Maffei Libonati; SOUZA, Marcelo Pereira de; SILVA, Flávio Roberto Matias da; FREIRE, Paulo Márcio Souza; GOLDSCHMIDT, Ronaldo Ribeiro. A Sentiment-Based Multimodal Method to Detect Fake News. In: BRAZILIAN SYMPOSIUM ON MULTIMEDIA AND THE WEB (WEBMEDIA), 1. , 2021, Minas Gerais. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 213-216.