Cyberbullying Detection Through Sentimental Analysis and NLP Techniques

R. S. Latha, R. Rajadevi, K. Logeswaran, G. R. Sreekanth, S. Arun Kumar, D. Praveen

2025

Abstract

Cyberbullying has become a major issue with the rise of social media, impacting mental health, especially among adolescents. Traditional content moderation methods struggle to manage the vast volume of posts generated daily, creating a need for efficient automated detection systems. This project explores advanced NLP and sentiment analysis techniques to detect harmful content in real-time. Using machine learning models like Random Forest , Logistic Regression , Decision Tree , Gradient Boost , Voting classifier , Naive Bayes ,the aim is to identify cyberbullying effectively. Preliminary findings show Random forest outperforms other models in accuracy and reliability. Future work will focus on improving precision, expanding datasets, and enabling real- time detection to foster safer online environment.

Paper Citation

in Harvard Style

Latha R., Rajadevi R., Logeswaran K., Sreekanth G., Arun Kumar S. and Praveen D. (2025). Cyberbullying Detection Through Sentimental Analysis and NLP Techniques. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 638-643. DOI: 10.5220/0013583100004664

in Bibtex Style

@conference{incoft25,
author={R. S. Latha and R. Rajadevi and K. Logeswaran and G. R. Sreekanth and S. Arun Kumar and D. Praveen},
title={Cyberbullying Detection Through Sentimental Analysis and NLP Techniques},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT},
year={2025},
pages={638-643},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013583100004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT
TI - Cyberbullying Detection Through Sentimental Analysis and NLP Techniques
SN - 978-989-758-763-4
AU - Latha R.
AU - Rajadevi R.
AU - Logeswaran K.
AU - Sreekanth G.
AU - Arun Kumar S.
AU - Praveen D.
PY - 2025
SP - 638
EP - 643
DO - 10.5220/0013583100004664
PB - SciTePress