Automatic Detection of Fake News: A Systematic Review

• Alice Barbosa IFCE
• Felipe Sousa IFCE
• Reinaldo Braga IFCE

DOI: https://doi.org/10.5753/ercemapi.2023.236262

Abstract

The adherence to social networks has allowed easy access to information with one click, offering mechanisms with a wide reach of dissemination in the Internet. However, the large volume of sharing, as well as the challenge of validating the veracity of the data, promotes a favorable environment for the proliferation of fake news. With the rise of Fake News, several studies have been carried out to identify fake news using Natural Language Processing. This article presents a systematic review of Brazilian and international studies on the detection of fake news. The results show that Twitter is the social network most studied by the articles and Support Vector Machine and Naive Bayes are the most applied classification algorithms.

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