Data mining applied in fake news classification through textual patterns

  • Marcos Paulo Moraes UFRJ
  • Jonice de Oliveira Sampaio UFRJ
  • Anderson C. Charles UFRJ


Fake news has been around for a long time. But with the advancement of social media and internet access, fake news has become a bigger problem. Because of the rapid spread in social media and instant messaging applications, fake news can reach more people in less time by directly influencing democratic processes, leveraging security issues that sometimes lead to tragic ends. In order to promote a fast and automated method of fake news identification, in this study, we performed an analysis of false Brazilian news, identifying writing patterns through natural language processing and machine learning.
Como Citar

Selecione um Formato
MORAES, Marcos Paulo; SAMPAIO, Jonice de Oliveira; CHARLES, Anderson C.. Data mining applied in fake news classification through textual patterns. In: ANAIS PRINCIPAIS DO SIMPÓSIO BRASILEIRO DE SISTEMAS MULTIMÍDIA E WEB (WEBMEDIA), 25. , 2019, Rio de Janeiro. Anais Principais do XXV Simpósio Brasileiro de Multimídia e Web. Porto Alegre: Sociedade Brasileira de Computação, oct. 2019 . p. 321-324.