Abstract: Our paper provides Detection of Cyberbullying using Machine Learning. In this project, we aim to build a system that tackles Cyberbullying by identifying the mean-spirited comments and also categorizing the comments as bullied one or not. The goal of this project is to show the implementation of software that will detect bullied tweets. As the social networking sites are increasing, cyberbullying is increasing day by day in everyone’s daily life who is using internet access. To identify such bullying tweets in the twitter handle we are going to make a software which will help to detect such mean type of comments with the help of Machine Learning model. As developing ML model, it will automatically detect the mean-spirited comments from the comment section. For this a Machine learning model is proposed to identify or detect and prevent the bullying on social media. As Machine Learning is used, we used two classifiers such as Naïve Bayes and SVM (Support Vector Machine) for training and testing the social median contents. Twitter API is used to fetch tweets and tweets are passed to the model to detect whether the tweets are bullying or not.
Keywords: Cyberbullying detection ∙ Machine Learning ∙ Twitter∙ Tweets ∙ Online harassment.
| DOI: 10.17148/IJARCCE.2022.11463