Detection of cyberbullying on social media using social media
Author(s):
Shanmukanjali, D. Arun praneeth kumar, P. Varsheek reddy, Dr.T.S.Mastan Rao
Keywords:
Abstract
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
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