Cyberbullying Detection using SVM Algorithm
Mr. Pushpak Deore1, Mr. Prathamesh Ahire2, Mr. Pranita Panpatil3, Mr. Chinmay Shinde4, Dr. P. D. Halle5
1 Student dept. of Information Technology SKN Sinhgad Institute of Technology & Science, Lonavala, Maharashtra
E-mail: deorepushpakk@gmail.com
2 Student dept. of Information Technology SKN Sinhgad Institute of Technology & Science, Lonavala, Maharashtra
E-mail: prathameshahire0123@gmail.com
3 Student dept. of Information Technology SKN Sinhgad Institute of Technology & Science, Lonavala, Maharashtra
E-mail: pranita2020p@gmail.com
4 Student dept. of Information Technology SKN Sinhgad Institute of Technology & Science, Lonavala, Maharashtra
E-mail: shindechinmay1234@gmail.com
5Asst. Dr, dept. of Information Tech, SKN Sinhgad Institute of Technology & Science, Lonavala, Maharashtra
E-mail: hallepriyanka2011@gmail.com
Abstract
Cyberbullying detection is a crucial field of research and technology development aimed at recognizing and mitigating instances of online harassment and abuse. This abstract offers a succinct overview of cyberbullying detection, emphasizing its significance and primary approaches. It involves the utilization of advanced algorithms, natural language processing techniques, and machine learning models to automatically identify and categorize potentially harmful online content, spanning text, images, videos, and digital communications. The importance of cyberbullying detection cannot be overstated, as it plays a pivotal role in safeguarding individuals, particularly young and vulnerable populations, from the emotional and psychological harm inflicted by online harassment. This review paper will delve into the specific approach of employing Support Vector Machine (SVM) algorithms for cyberbullying detection, examining its strengths, challenges, and future prospects.
Keywords: Cyberbullying, Detection, SVM Algorithm, Online Harassment, Machine Learning, Natural Language Processing, Feature Extraction,AES ,Classification,Model-training
