Detection of cyberbullying on social media using social media
Shanmukanjali, D. Arun praneeth kumar, P. Varsheek reddy, Dr.T.S.Mastan Rao
In the realm of online social networks, it is crucial to conduct research on the detection of anonymous user behavior and offensive content. This particular project focuses on detecting bully statements and offensive data in shared content of social networks. To achieve accurate results, the project proposes a system called “Cyber Bullying Detection (CBD) in Social Networking,” which utilizes Machine Learning algorithms and Text Mining concepts. The project employs two datasets, namely the ‘Hate Speech and Offensive Language Dataset’ and ‘Harassment-Corpus Dataset,’ and utilizes three Machine Learning classifiers, including Support Vector Machine (SVM), Random Forest (RF), Naïve Bayes (NB), and Neural Network (NN) Algorithms to compare their performance on both datasets. The project also includes the design and development of a Python-based Django web application to demonstrate the system's results.
Article Details
Unique Paper ID: 159121

Publication Volume & Issue: Volume 9, Issue 11

Page(s): 459 - 466
Article Preview & Download

Share This Article

Join our RMS

Conference Alert

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

Latest Publication

Call For Paper

Volume 10 Issue 10

Last Date for paper submitting for March Issue is 25 June 2024

About Us enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on

Social Media

Google Verified Reviews