Citation

Silva CVM, Fontes RS, Júnior MC. J. Appl. Secur. Res. 2021; 16(2): 168-189.

Copyright

(Copyright © 2021, Informa - Taylor and Francis Group)

DOI

10.1080/19361610.2020.1761224

PMID

unavailable

Abstract

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.

Language: en

Keywords

Computational and Artificial Intelligence; fake news; machine learning; public security