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Fraud Account Detection on Social Network using Machine Learning Techniques

E. Anupriya, N. Kumaresan, V. Suresh, S. Dhanasekaran, K. Ramprathap, P. Chinnasamy

202213 citationsDOI

Abstract

Nowadays, a person's impact is frequently determined by the number of followers he or she has on social media. To this aim, the prevalence of false accounts is one of the most pressing issues, with the potential to disrupt a wide range of real-world and economic activity. Bot followers are dangerous to social media as these could alter perceptions of popularity and influence, which can have a ample amount of impact on every sector. As a result, new approaches must be developed to enable the detection and classification of bogus accounts. This study gives novel method for distinguishing original profiles. The method uses information gathered automatically from huge data to characterize typical patterns of fake account.

Topics & Concepts

PopularityComputer scienceSocial mediaRange (aeronautics)Machine learningData scienceArtificial intelligencePerceptionData miningComputer securityWorld Wide WebEngineeringPsychologyNeuroscienceAerospace engineeringSocial psychologySpam and Phishing DetectionNetwork Security and Intrusion DetectionBlockchain Technology Applications and Security
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