SOK: Fake News Outbreak 2021: Can We Stop the Viral Spread?
- URL: http://arxiv.org/abs/2105.10671v1
- Date: Sat, 22 May 2021 09:26:13 GMT
- Title: SOK: Fake News Outbreak 2021: Can We Stop the Viral Spread?
- Authors: Tanveer Khan, Antonis Michalas, Adnan Akhunzada
- Abstract summary: Social Networks' omnipresence and ease of use has revolutionized the generation and distribution of information in today's world.
Unlike traditional media channels, social networks facilitate faster and wider spread of disinformation and misinformation.
Viral spread of false information has serious implications on the behaviors, attitudes and beliefs of the public.
- Score: 5.64512235559998
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Social Networks' omnipresence and ease of use has revolutionized the
generation and distribution of information in today's world. However, easy
access to information does not equal an increased level of public knowledge.
Unlike traditional media channels, social networks also facilitate faster and
wider spread of disinformation and misinformation. Viral spread of false
information has serious implications on the behaviors, attitudes and beliefs of
the public, and ultimately can seriously endanger the democratic processes.
Limiting false information's negative impact through early detection and
control of extensive spread presents the main challenge facing researchers
today. In this survey paper, we extensively analyze a wide range of different
solutions for the early detection of fake news in the existing literature. More
precisely, we examine Machine Learning (ML) models for the identification and
classification of fake news, online fake news detection competitions,
statistical outputs as well as the advantages and disadvantages of some of the
available data sets. Finally, we evaluate the online web browsing tools
available for detecting and mitigating fake news and present some open research
challenges.
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