Identification of social media cyberbullying with the aid of machine learning

The internet, a vast platform for communication and idea-sharing, hosts around 4 billion users on social media platforms. Unfortunately, this widespread digital landscape has witnessed a surge in online abuse, harassment, trolling, and cyberbullying. These issues have far-reaching consequences, including depression, self-harm, and, tragically, suicide. Cyberbullying, involving negative, false, or harmful content targeting individuals, has severe implications, especially for the mental health of the younger generation. We propose the CBSA (Cyberbullying with Sentiment Analysis) model, which leverages a range of features to enhance cyberbullying detection.