  Cyberbullying or Online harassment detection on social media for various
major languages is currently being given a good amount of focus by researchers
worldwide. Being the seventh most speaking language in the world and increasing
usage of online platform among the Bengali speaking people urge to find
effective detection technique to handle the online harassment. In this paper,
we have proposed binary and multiclass classification model using hybrid neural
network for bully expression detection in Bengali language. We have used 44,001
users comments from popular public Facebook pages, which fall into five classes
- Non-bully, Sexual, Threat, Troll and Religious. We have examined the
performance of our proposed models from different perspective. Our binary
classification model gives 87.91% accuracy, whereas introducing ensemble
technique after neural network for multiclass classification, we got 85%
accuracy.
