APPLICATION OF NEURAL NETWORKS FOR CYBERBULLYING DETECTION

Abstract

Cyberbullying is a global problem affecting many people, especially children and teenagers. This phenomenon is common in many countries, causing psychological, emotional and social damage to its victims. Technologies such as social media and mobile apps exacerbate the problem by providing a platform for anonymous attacks. To resist cyberbullying, many organizations and governments are taking action, from zero-tolerance policies to legislative initiatives. Awareness raising and education also play a key role. At the forefront of the fight against cyberbullying is the development of neural networks that can automatically detect and block toxic content online. This article describes the main stages of training a neural network and creating an information technology based on it to protect people from such a phenomenon as cyberbullying.