Fake News Detection on Social Networks: A Survey
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Published:2023-10-30
Issue:21
Volume:13
Page:11877
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ISSN:2076-3417
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Container-title:Applied Sciences
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language:en
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Short-container-title:Applied Sciences
Author:
Shen Yanping1, Liu Qingjie1, Guo Na1, Yuan Jing1, Yang Yanqing2ORCID
Affiliation:
1. School of Information Engineering, Institute of Disaster Prevention, Beijing 101601, China 2. College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China
Abstract
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.
Funder
The Fundamental Research Funds for the Central Universities
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
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