Social Networking Sites Fake Profiles Detection Using Machine Learning Techniques
Abstract
In the present paper, we offer a model that might be applied to identify if an account is real or false. It is unnecessary to manually examine each account because our model, which uses a support vector machine as a classification technique, can simultaneously process an extensive accounts dataset. We are concerned with the community of fake accounts, and our issue is classification and clustering. We employ artificial neural networks (ANN) and machine learning (ML) to assess the likelihood that a Facebook friend request is genuine or not. The existence of bots and phoney profiles is another risk factor for personal data being collected for illicit purposes. Bots are computer programmers that can compile data about users without their knowledge. Web scraping is the term for this activity. The fact that this behaviour is legal makes it worse. Bots can be disguised or appear as false friend requests to access private information on a social networking site. Still, there is a 7% false positive rate in which our system fails to identify a fake profile correctly.
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