A Sentiment-Based Multimodal Method to Detect Fake News - Maia, Igor Maffei Libonati; Souza, Marcelo Pereira de; Silva, Flávio Roberto Matias da; Freire, Paulo Márcio Souza; Goldschmidt, Ronaldo Ribeiro (Proceedings of the Brazilian Symposium on Multimedia and the Web (WebMedia); 2021: Proceedings of the 27th Brazilian Symposium on Multimedia and the Web, 2021)
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.