Fake News Detection on Social Networks: A Survey

被引：1
|
作者：
Shen, Yanping [1 ]
Liu, Qingjie [1 ]
Guo, Na [1 ]
Yuan, Jing [1 ]
Yang, Yanqing [2 ]
机构：
[1] Inst Disaster Prevent, Sch Informat Engn, Beijing 101601, Peoples R China
[2] Xinjiang Univ, Coll Informat Sci & Engn, Urumqi 830046, Peoples R China
来源：
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 21期
关键词：
fake news; detection; dataset; social networks; LINGUISTIC FEATURES; FRAMEWORK;
D O I：
10.3390/app132111877
中图分类号：
O6 [化学];
学科分类号：
0703 ;
摘要：
In recent years, social networks have developed rapidly and have become the main platform for the release and dissemination of fake news. The research on fake news detection has attracted extensive attention in the field of computer science. Fake news detection technology has made many breakthroughs recently, but many challenges remain. Although there are some review papers on fake news detection, a more detailed picture for carrying out a comprehensive review is presented in this paper. The concepts related to fake news detection, including fundamental theory, feature type, detection technique and detection approach, are introduced. Specifically, through extensive investigation and complex organization, a classification method for fake news detection is proposed. The datasets of fake news detection in different fields are also compared and analyzed. In addition, the tables and pictures summarized here help researchers easily grasp the full picture of fake news detection.
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页数：19
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