Técnicas de reconhecimento e combate a notícias falsas na Internet: um mapeamento sistemático

Abstract

With the universalization of access to the internet and the globalization of social media, false news travels fast on the internet, capable of changing the news ecosystem. Thus, the objective of this work is to investigate which tools, methods or strategies are available for recognizing and combating false news on the internet, as well as showing which of these tools have been shown to be more efficient. The research methodology adopted is based on the principles of Experimental Software Engineering, which is based on conducting a secondary study: Systematic Mapping. The results obtained showed that the models are based on machine learning and deep learning, using text classification methods, being evaluated by different validation metrics with excellent results.