Logistic Regression Based Cyber Harassment Identification

Increased online use and allowing users to engage with groups such as digital networking have contributed the growth of hacking. Online abuse is a new type harassment that has lately become more prevalent communities grown in popularity. It tends send messages which included defamatory claims or vocally harassing someone while internet group. Only if modern civilization recognizes it truly is, countless hidden sufferers may continue suffer. There been several studies on cyber bullying, but none them able offer solid remedy. By creating model can recognize block bullying-related incoming outgoing communications, we address this issue our project. employing supervised classification techniques an open source dataset carefully annotated, hope provide lexical baselines for job. We employed logistic regression classifier training identifying instances bullying behaviors. The used twitter collected from kaggle. Our classifies message whether it’s not.