AI-Powered Smart Social Content Filter for Identifying Harmful Online Content

Social media platforms, which have become vital for global communication in this quickly changing digital landscape, are also a breeding ground for harmful content, such as hate speech, false information, and explicit content. This study looks into the creation and application of automated AI-based content moderation systems to make online spaces safer. We concentrate on methods for identifying and reducing harmful content by utilizing developments in NLP (Natural Language Processing) and ML (Machine Learning). Our method improves the precision and effectiveness of moderation procedures by combining text and image analysis. In this study, ethical considerations are crucial because they guarantee that the AI systems are just, open, and consistent with society norms. We show how AI has the potential to drastically cut down on harmful content on social media through rigorous testing and Python programming.