부산대학교 도서관

Online Social Networks OSNs have become more popular among individuals in today's society for usage in their regular social activities. Because of this, a significant amount of information on the users' social lives, personal lives, and professional lives is being saved on these OSNs. The growth of bogus profiles is one of the problems associated with utilizing these sites, despite the fact that they have improved the quality of people's social lives. Other problems are also associated with their use. The user data that is made accessible on OSNs is drawing the attention of academics and social analyzers, but it is also attracting the attention of hackers. These cybercriminals take advantage of the openness and vulnerability of an OSN by creating phoney identities, then use those profiles to engage in illegal, deceptive, and destructive behavior. Some examples of this behavior include identity theft, defamation, trolling, bullying, and spamming. In this research Paper, we will examine a variety of methods, both supervised and unsupervised, for determining if an Instagram profile is authentic or false. After putting a number of readily accessible Machine Learning Models through their paces, we have developed a Hybrid Model, which can be found in the file Maulik Shah Fake Profile Identifier.ipynb. This dataset has room for improvement in terms of quantity and quality metrics; however, this paper also demonstrate how accurate it can become to identify fake profile.