Intelligent Fake News Detection: A Systematic Mapping

被引：18
|
作者：
Meneses Silva, Caio, V [1 ]
Fontes, Raphael Silva [1 ]
Colaco Junior, Methanias [1 ]
机构：
[1] Univ Fed Sergipe, Comp Dept, Marechal Rondon Ave S-N, BR-49100000 Sao Cristovao, Sergipe, Brazil
来源：
JOURNAL OF APPLIED SECURITY RESEARCH | 2021年 / 16卷 / 02期
关键词：
Computational and Artificial Intelligence; machine learning; fake news; public security; BIG DATA;
D O I：
10.1080/19361610.2020.1761224
中图分类号：
DF [法律]; D9 [法律];
学科分类号：
0301 ;
摘要：
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.
引用
收藏
页码：168 / 189
页数：22
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