Detection of Fake Profiles in Online Social Networks – A Survey
6 Pages Posted: 27 Jul 2022 Last revised: 10 Aug 2022
Date Written: July 14, 2022
Abstract
In the today’s world, almost everybody from a child to an old-age person are spending a good amount of time on Online Social Networks (OSNs) by interacting and exchanging their information with the other people in the world. Because of the massive interconnectivity and the large amount of information sharing provided by OSN, many people also tend to misuse the platform of social networks. One of the ways in which people misuse the social networks is by creating several fake accounts for taking various types of immoral benefits such as targeting a particular user, or attempting any other cybercrime. This motivates the need fordeveloping a system that is able to identify fake accounts on the social networks. Researchers have made several attemptsfor detecting the fake/real accounts on social networkingsites by using various classification algorithms with various account’s features such as timebased, graphbased,contentbased, and user-based features. In this work,we have provided an overview of major studies done in this field along with the suggestions regarding what can be done in future in this field. We have summarized the recent advancements done in this field using machine learning and deep learning algorithms, which could help the future researcher to develop a foundation in this field.
Keywords: Fake Account Detection,Feature Extraction, Classification, Online Social Network, OSN.
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