Identification of Fake accounts in social media using machine learning
Kotra Shreya, Amith Kothapelly, V Deepika, Shanmugasundaram Hariharan
Abstract
Fake profiles are used in advanced persistent threats and are also used in other nefarious activities. As we all know, Globally, billions of individuals utilize Social networking sites like Facebook, Twitter, LinkedIn, Instagram, etc. to establish connections. A new era of networking has been ushered in by social networks simplicity and accessibility. At the same time, various types of scammers are drawn to these social media platforms. These scammers make fake profiles to spread their content and carry out scams. In this project, we used Deep Neural Networking and Machine Learning algorithms namely Artificial Neural Networks(ANN), Random Forest and Support vector machine(SVM) algorithms to assess the likelihood that Facebook account information is accurate or not. The dataset used in this paper is taken from GitHub which is a Facebook profile Dataset to identify faux and genuine profiles, also we have described the associated classes and libraries. Here we are going to predict the faux and real profiles using the best accurate model after comparing the outcomes of the three techniques employed.