This project develops a Spam Comment Detection and User Blocking System for a social media web application, designed to enhance user experience and maintain a secure online environment. Users can register, log in, send friend requests, chat, and post text or images, which may receive likes, dislikes, and comments. The system employs an advanced classifier algorithm to detect and filter negative or spam comments in both the chat and post sections. If a user exceeds 10 spam attempts, their IP address is blocked, preventing further access to the platform. Users can also create and share local events, which are visible to other users. The admin has oversight capabilities, including viewing user activity, managing events, and monitoring time spent on the platform through graphical analysis. The admin can also intervene by sending warnings to users displaying addictive behavior. The system integrates HAM algorithms and Bloom Filter data structures to improve spam detection efficiency and ensure optimal performance. This solution helps foster a safe, interactive environment by reducing harmful content and promoting responsible usage.
R et al. (Thu,) studied this question.