Abstract: Cyberbullying refers to the use of electronic techniques of intimidation. Historically challenging, there has been a growing awareness of the repercussions for young people. Teenagers and young adults who spend time on social media sites are an easy target for bullies because of the platform’s conducive nature to harassment and threats. We can create algorithms that can automatically identify cyberbullying material and distinguish between the language styles of cyberbullies and their victims with the use of machine learning techniques. Over the last decade, social media has seen explosive growth, which has benefits and drawbacks. As the number of social media sites and apps continues to grow, more and more people are able to connect with one another online. directly, ignoring cultural and economic contexts While there are numerous positive outcomes associated with social media use, none exist at this time. The increase of hate speech over the last several years is a special issue that has surfaced. The use of foul language is the major component of hateful statements. Online networking use It might be used to refer to anybody or anything at all. collective of like-minded people. The methods we use to deal with hostility and the steps we take to mitigate it were detailed in this study. People\’s instantaneous expressions of wrath and animosity on social media are harmful to the sentiments of others. In-depth investigation on the handling of The most accurate machine learning and natural language processing techniques were used to choose the model used to exclude hate speech.

Published in: International Journal for Research in Applied Science and Engineering Technology (IJRASET)