ABSTRACT
Online social media networks are becoming popular with great speed in this generation, and people’s personal lives are becoming more closely linked to these sites. People use these networks to share videos, read news articles, advertise for products, etc. With the increasing growth of these networks, a huge quantity of a user’s data can attract attackers and these attackers then can share false news and spread malicious lies. In addition, these social networking sites are now becoming a target medium for attackers to spread an enormous amount of false data. On account of this, researchers have begun to explore effective techniques for detecting these kinds of activities and fake accounts based on the classification methods. In this paper, different techniques of machine learning are explored to provide successful identification of a fake account. Various machine learning algorithms are used to solve such a problem with pre-processing techniques to identify fake accounts. Finally, the machine learning techniques are also compared, and the proposed approach provides better results than the previously used techniques to detect fake user accounts on these online social media networks
