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@article{172345,
        author = {Raghavendra T S and GADE PRANAV REDDY and VELICHALAMALA SUMA VARSHA and SANGARAJU LAKSHMI PRASANNA and MOPURI CHANDRA PRAJWAL},
        title = {Billy Buddy against Cyber Bullying},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {8},
        pages = {2911-2918},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=172345},
        abstract = {Billy Buddy against Cyber Bullying" basically deals with providing a safe online space to tackle cyberbullying, comprising two major modules: Admin and User. The Admin module comprises secure login, state-wise data analysis, and user management, while the User module allows sign-up, incident reporting, discussion with others who have resolved similar issues, and marking problems as solved. The platform provides the users with a password recovery option via OTP, profile management, and uses an advanced machine learning algorithm which includes Random Forest, MLP Classifier, and AdaBoost for the detection and classification of cyberbullying. It is developed in Python, MySQL, and Django, with an intuitive interface in HTML, CSS, and JavaScript. "Billy Buddy against Cyber Bullying" aims at a helpful environment where the user can report and resolve incidents of cyberbullying by making use of advanced technology to counter this serious social issue and to make the digital world a safer place.},
        keywords = {Cyberbullying, Machine Learning, Random Forest, MLP Classifier, AdaBoost, Flask, Django, MySQL, Python, User Module, Admin Module, Problem Registration, Chat Support, Profile Management, State-wise Analysis, Data Classification, Web-based Platform, Cyberbullying Prevention, User Interaction, Secure Login, Dashboard, Sentiment Analysis.},
        month = {January},
        }