Ensemble Learning Based Prediction for Cyber Harassment Observations on Tweets

Now a days social media plays crucial role in allowing individuals to express their views. Based on their views find the information of different keywords/statements like sadness, happiness, teasing, harassment and abuse. Online abuse, a novel form of pestering, have become increasingly predominant in online groups in modern civilization. Detecting harassment is indeed a significant challenge. Several studies provide information on cyber harassment, but none of them offer a solid remedy. Several studies provide information on cyber harassment, but none of them offer a solid remedy. Due to this reason, multiple models can be practiced to recognize and block harassment-related communications. We have utilized ensemble machine learning models to predict accurate results. The twitter dataset used for our research. We observe two models getting accuracy for RF+DT is 92% and SVM+LR is 93%. It is similar accuracy in individual models. So, there is no difference between Ensemble or individual model accuracy rate.