Fake News in Virtual Community, Virtual Society, and Metaverse

A Survey

Bibliographic Data

ID22106936
AuthorsJinxia Wang (0000-0002-8768-2707, Art Design College, Shaanxi Fashion Engineering University, Xi’an, China), Stanislav Makowski (University of Warsaw), Alan Cieślik (University of Warsaw), Haibin Lv (0000-0003-1059-4765, National Bureau of Statistics of China), Zhihan Lv (0000-0003-2525-3074, Uppsala University)
Year2024
Volume11
Issue4
Pages4828-4842
Publication date2024-08-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueIEEE Transactions on Computational Social Systems (JOURNAL)
Journal identifiersISSN: 2329-924X • E-ISSN: 2373-7476
PublisherInstitute of Electrical and Electronics Engineers (IEEE) (PUBLISHER)
DOI10.1109/tcss.2022.3220420
OpenAlexW4319303120
LanguageEN
Citations received5
References cited101

In the trend of the accelerated progression of communication network technology, the emergence of virtual communities (VCs), virtual societies (VSs), metaverse, and other technologies not only makes data access and sharing easier but also leads to the proliferation of fake news (FN). To effectively monitor and identify FN in VC, VS, and metaverse, and to create a safer virtual space, this work takes FN in VC, VS, and metaverse as objects. First, the content and display methods of FN are reviewed and explained, and it is understood that FN is mainly displayed by single-modal and multimodal representations. Second, the application scenarios in many important fields such as transportation are reviewed and analyzed, so as to further understand the impact and detection effect of FN in different scenarios. Finally, an intelligent outlook and summary analysis are carried out on the detection and information security of FN, which provides theoretical reference and new opportunities for the detection and identification of FN in the virtual cyberspace

Computer security · Cyberspace · Data science · Human–computer interaction · Metaverse · Modal · SAFER · The Internet · Virtual reality · World Wide Web · Advanced Malware Detection Techniques · Computer Science · Misinformation and Its Impacts · Spam and Phishing Detection