A machine learning based preventing the occurrence of cyber bullying messages on OSN

Abstract

The process of threaten or harassment of any user with the help of posting wrong/abused or vulgar messages using the social media in the internet is known as Cyber bullying .These messages may sometime contain a text posted by a teen, or preteen or a child who want to threaten or harassed or embarrassed other child by posting the messages. So in this project, we mainly try to propose another depiction learning strategy to handle this issue known as SEMdae. Here the semantic augmentation comprises of predefined words that contain noise or abused meaning which is posted into the database by the admin and these words are classified based on the five categories that are available in the literature like “HATE, VULGAR, OFFENSIVE, SEX, and VOILENCE”.