Application of Machine Learning Techniques in Detecting Fake Profiles on Social Media

Today, almost billions of people use social media sites to share pictures, thoughts online and connect to people worldwide. During this challenging time of pandemics, we are leaning towards social media more than ever, increasing our engagement. It has made us aware of the coronavirus cases worldwide, has entertained us, helped us stay connected to our acquaintances living far away, and even helped many to start and grow their small businesses online. Besides the wide range of advantages that social media offers, it also comes up with many disadvantages of being an online platform. Issues like fake profiles and impersonation have increased on social media platforms, such as computer-generated bots, human-generated, or cyborgs. Such accounts are made with malicious intentions. Moreover, there is no feasible solution to such a problem. The paper aims at developing a model which can detect fake profiles on social media by using machine learning techniques for better prediction and identification. For this paper, Instagram data is considered for the availability of the dataset, and the analysis will be done by implementing the machine learning algorithms, which gives the highest accuracy on the dataset. By accurately detecting such profiles, social media platforms can be made safe for users.