An Intelligent Toxic Language Detection and Smart Content Moderation System Using Transformer-Based NLP Models

This paper presents an intelligent toxic language detection and smart content moderation system using transformer-based natural language processing models. The proposed approach integrates a fine-tuned DistilBERT classifier with rule-based linguistic refinement techniques to detect and mitigate toxic content while preserving semantic intent. The work is submitted as an academic research paper for project evaluation and assessment purposes.