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September 10, 2025

A Comparative Analysis of Machine Learning Techniques for Cyberbullying Detection

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This research compares supervised learning methods for detecting cyberbullying in youth on social media, suggesting improved technologies.

The study reveals effective machine learning techniques can improve cyberbullying detection on social media platforms.
Key metrics like accuracy and F1-score were assessed across various models including Naive Bayes and Random Forest.
Analysis involved publicly available Twitter data, processed with vectorization techniques for model training.
This work highlights the importance of fine-tuning models, which can significantly enhance detection effectiveness in real-world applications.

Barhate et al. (2025) studied this question.

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This research compares supervised learning methods for detecting cyberbullying in youth on social media, suggesting improved technologies.