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Detection and Classification of Genuine User Profile Based on Machine Learning Techniques

Prathyakshini,Pratheeksha Hegde N,Nikitha Saurabh,P. K

Published 2022 in 2022 2nd International Conference on Intelligent Technologies (CONIT)

ABSTRACT

The current era is driven by online social networks which have evolved as a popular virtual communication platform among people. Social media users often share pictures, videos and express their views on various matters through social media posts. Though online social networks have succeeded in helping people to interact and build connections worldwide virtually, it also exposes the user to different kinds of cyber frauds. Hence identifying a genuine user profile on social media has gained significant importance in the lieu of detecting social media users from cyber criminals. With this regard, this paper is focussed at developing a machine learning model that identifies and classifies user profiles as genuine or not genuine categories. The experiment outcome shows that the proposed model achieved an average accuracy of 95% in the classification task considering all three datasets.

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