Techniques to Detect Fake Profiles on Social Media Using the New Age Algorithms - A Survey

This research explores the growing issue of fake accounts in Online Social Networks [OSNs]. While platforms like Twitter, Instagram, and Facebook foster connections, their lax authentication measures have attracted many scammers and cybercriminals. Fake profiles conduct malicious activities, such as phishing, spreading misinformation, and inciting social discord. The consequences range from cyberbullying to deceptive commercial practices. Detecting fake profiles manually is often challenging and causes considerable stress and trust issues for the users. Typically, a social media user scrutinizes various elements like the profile picture, bio, and shared posts to identify fake profiles. These evaluations sometimes lead users to conclude that a profile is indeed fake. Many ongoing research endeavors focus on new-age machine learning algorithms identifying fake profiles by examining elements such as the profile picture, and the content shared, including fake news or reviews, and distinguishing whether the profile is operated by a social bot or a real person. Our paper aims to comprehensively discuss and compile these diverse methods, providing an understanding of existing techniques for future studies.