Spammer Detection and Fake User Identification on Social Networks Using Python

Abstract

Social networking platforms have become one of the most popular communication mediums worldwide. However, these platforms are increasingly affected by spammers and fake user accounts that spread misinformation, malicious links, advertisements, and harmful content. Detecting such fake accounts manually is difficult due to the massive volume of users and posts generated daily. This project proposes a Python-based machine learning system to detect spammers and identify fake users on social networks. The system analyzes various user profile attributes such as number of followers, number of posts, account activity patterns, and content characteristics. Using machine learning classification algorithms, the model distinguishes between genuine users and spammers. The proposed system helps social networking platforms maintain security, reduce spam content, and improve user experience by automatically identifying suspicious accounts.