Identification of Forged Profiles in Online Social Networks Using Machine Learning and NLP

Abstract

Abstract: Many people today use social networking sites as a part of their everyday lives. They create their own profiles on the social network platforms every day, and they interact with others regardless of their location and time. In addition to providing users with advantages, social networking sites also present security concerns to them and their information to them. We need to classify the social network profiles of the users to figure out who is encouraging threats on social networks. From the classification, we can figure out which profiles are genuine and which are fake. As far as detecting fake profiles on social networks is concerned, we currently have different classification methods. However, we must improve the accuracy of detecting fake profiles in social networks. We propose the use of a machine learning algorithm and Natural Language Processing (NLP) technique in this paper so as to increase the detection rate of fake profiles. This can be achieved using Support Vector Machines (SVM) and Naïve Bayes algorithms.