FAKE PROFILES IDENTIFICATION IN ONLINE SOCIAL NETWORKS USING MACHINE LEARNING AND NLP

Abstract

Social media is an integral part of most people's everyday routines nowadays. All hours of the day and night, countless people join social media sites to connect with others and share information. Although social media sites have many positive uses, they also pose risks to users' personal information. In order to find out who is spreading threats on social media, we need to classify user profiles. Classification allows us to differentiate between authentic and fake social media profiles. The detection of fake social media accounts has long made use of a number of classification schemes. On the other hand, we need to improve the precision with which social media platforms identify fake profiles. Using methods from machine learning and natural language processing (NLP), this study aims to improve the false profile identification accuracy rate. Support Vector Machine (SVM) and the Naïve Bayes technique are both applicable.