Intelligent Fake News Detection: A Systematic Mapping

Context: The speed with which the Fake News spread today has encouraged work in various areas to minimize the damage and the public insecurity caused by their proliferation. Objective: To characterize and analyze Fake News threat detection. Method: Systematic Mapping, since the area youthfulness still prevents a complete meta-analysis. Results: The most used algorithms were LSTM (17.14%), Naive-Bayes and Similarity Algorithm (11.43%). Conclusions: There is still the absence of more controlled experiments in the Big Data context. Fake News is a national security problem, requiring effective solutions to combat it. Situations like the Covid-19 virus (coronavirus) reinforce this fact.