AN AUTOMATIC CYBERBULLYING DETECTION MODEL IN TWITTER SOCIAL MEDIA- BUSINESS APPLICATION BASED ON BIDIRECTIONAL COOT OPTIMIZED GATED RECURRENT UNIT

Abstract

Cyberbullying (CB) is an electronic type of bullying in which a group or a person engages in purposeful and aggressive behaviour towards another group or individual on social media platforms. It contains hate messages that are spread by social media, emails, and other means on personal or public computers, as well as personal mobile phones. The hypothesized differences between CB and traditional bullying show that CB findings from traditional bullying are insufficient. With its rising frequency, CB has had a psychological and physical impact on victims. To limit the risk in smart cities, it is critical to recognize the CB context and its applications. However, from the perspective of the cyber world, the application using CB has challenges such as a lack of awareness of aggressors and their identities, a lack of direct communication, and linking repercussions to others. Hence, this work gives a new cyberbullying detection model to automatically classify the tweets using optimized deep learning