当前位置: X-MOL 学术Journal of Applied Security Research › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Intelligent Fake News Detection: A Systematic Mapping
Journal of Applied Security Research Pub Date : 2020-05-14 , DOI: 10.1080/19361610.2020.1761224
Caio V. Meneses Silva 1 , Raphael Silva Fontes 1 , Methanias Colaço Júnior 1
Affiliation  

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.



中文翻译:

智能假新闻检测:系统映射

摘要

语境

如今,假新闻传播的速度加快,鼓励在各个领域开展工作,以最大程度地减少扩散造成的破坏和公众不安全感。

客观的

表征和分析“假新闻”威胁检测。

方法

系统化制图,因为该区域的年轻状态仍然无法进行完整的荟萃分析。

结果

最常用的算法是LSTM(17.14%),朴素贝叶斯和相似性算法(11.43%)。

结论

在大数据环境中仍然缺乏更多可控制的实验。假新闻是一个国家安全问题,需要有效的解决方案来应对。诸如Covid-19病毒(冠状病毒)之类的情况进一步证明了这一事实。

更新日期:2020-05-14
down
wechat
bug