CYBER BULLYING DETECTION USING MACHINE LEARNING AND DEEP LEARNING

The use of information and technology to bully a person online is referred to as cyberbullying. Individuals use Information and Communication Technology (ICT) to ridicule, embarrass, taunt, defame, intimidate, and criticise a person without making a direct eye contact. With the rise of social media, bullies have created a “virtual playground” in Facebook, Instagram, WhatsApp, Twitter and YouTube by targeting specific set of individuals or groups. It is necessary to deploy models and mechanisms in place for bullying contents, where the content is automatically detected and resolved, as the repercussions could have societal ramifications. This paper proposes a unique hybrid model for detecting cyberbullying in three different types of social media content such as textual, visual, and infographic data