Which machine learning paradigm for fake news detection?

被引：17
|
作者：
Katsaros, Dimitrios [1 ,2 ]
Stavropoulos, George [3 ]
Papakostas, Dimitrios [3 ]
机构：
[1] KIOS Ctr Excellence, Nicosia, Cyprus
[2] Univ Cyprus, Nicosia, Cyprus
[3] Univ Thessaly, Volos, Greece
来源：
2019 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE (WI 2019) | 2019年
关键词：
Fake news; machine learning;
D O I：
10.1145/3350546.3352552
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Fake news detection/classification is gradually becoming of paramount importance to out society in order to avoid the so-called reality vertigo, and protect in particular the less educated persons. Various machine learning techniques have been proposed to address this issue. This article presents a comprehensive performance evaluation of eight machine learning algorithms for fake news detection/classification.
引用
收藏
页码：383 / 387
页数：5
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