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The use of derogatory and combative language has dramatically expanded in the social media and networking
era. Young people are largely responsible for it. More than half of the young people who use social media are
victims of cyber bullying. Insults in social media websites create negative interactions within the network.
These comments foster a disrespectful atmosphere in internet. Online harassment, including the dissemination
of private chats, rumours, and sexual insults, has recently been the cause of numerous instances all around the
world. As a result, academics are paying more and more attention to the detection of bullying text or message
on social media. In order to classify such comments in a practical way, the study aims to uncover techniques
to recognise bullying in text by analysing and experimenting with various methodologies. The goal of this
research is to combine machine learning and natural language processing to create a powerful method for
identifying online bullying and abusive messages. In order to discover bullying tests and hostile comments,
we devised an effective algorithm, and we analysed these comments to ensure their validity.