Spam Detection and Fake User Identification Using Machine Learning Algorithm

The rise of online platforms and social networks has brought about an exponential increase in the amount of spam content and the proliferation of fake user accounts. These malicious activities pose significant threats to the integrity, security, and user experience of online communities. Consequently, there is a pressing need for effective techniques to detect and mitigate spam and identify fake user accounts. This project proposes a comprehensive approach to tackle spam detection and fake user identification through the application of advanced machine learning and data analysis techniques. The primary objective is to develop a robust system capable of accurately detecting and flagging spam content, as well as identifying and removing fake user accounts from online platforms.