Application of Machine Learning in Detecting Dangerous Content on Facebook Social Media Applications to Protect Teenagers on Social Media

Abstract

This study investigates the utilization of machine learning techniques to identify harmful content on the social media platform Facebook, with a particular focus on protecting teens in their social media interactions. The rise of social media has exposed young users to a variety of risks, including cyberbullying, hate speech and inappropriate material. By developing machine learning models trained on a diverse dataset of text, images and videos shared on Facebook improves content moderation efforts to protect teens from exposure to harmful content. Through the application of natural language processing and image recognition algorithms, the model will classify content based on pre-defined categories of harmful material. It is hoped that these findings will contribute to the advancement of content moderation systems on social media platforms, and encourage a safer online environment for teenage users.