Abstract:
On the internet, the number of cyberbullying importunity in the Bangla language is adding
in a noteworthy way. All kinds of people like men, women and youths are being the victims
of cyberbullying substantially through social medias. There's hardly the system of
discovery on the cyberbullying in Bangla language. My ideal is to descry cyberbullying
and to argue out of the bullying using machine learning. To complete this ideal there's the
need of Bangla dataset, but unfortunately this dataset is veritably rare to find. So I collected
the data from Youtube, Facebook etc. using some scrapper tools. The dataset is labelled as
cyberbullying “ YES” or “ NO”. Machine learning is the stylish way of approach for my
work. I've used many a type of algorithms like Natural Language Processing (NLP),
Logistic Regression (LR), Multinomial Naïve Bayes (MNB), Support Vector Classifier
(SVC), Random Forest Classifier (RFC), Decision Tree Classifier, KNeighbors Classifier,
AdaBoost Classifier, Bagging Classifier, ExtraTreeClassifier, GradeintBoosting Classifier,
XGB Classifier. After applying all these algorithms, the exactitude is plant in Logistic
Regression (LR) 89.81%, Multinomial Naïve Bayes (MNB) 89.38%, Support Vector
Classifier (SVC)90.0%, Random Forest Classifier (RFC) 89.91%, Decision Tree Classifier
86.39%, GradeintBoosting Classifier 89.81%. And the maximum exactitude in Support
Vector Classifier (SVC), Which is 90.0%
