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Real-Time Cyberbullying Detection System by ashoka6122002 is a document available to read on EtoBox.

What is Real-Time Cyberbullying Detection System about?

This project developed a machine learning-based system to detect cyberbullying in real-time using tweets, focusing on accuracy and scalability. The Support Vector Machine (SVM) classifier outperformed Naive Bayes, achieving 71.25% accuracy, and the system was integrated with the Twitter API for real-time classification. A timeline-based validation mechanism was also implemented to enhance accuracy by analyzing multiple tweets from users for consistent bullying behavior.

Author

ashoka6122002

Language

EN