Multilingual Profanity Filtering: Advanced Tools for Effective Content Moderation on Digital Platforms

Multilingual profanity filtering has become a critical challenge as digital platforms grow globally. Tools like GitHub's readme-SVG/Banned-words use language-specific lexicons and ML models to detect banned words across languages, but face limitations from static datasets, linguistic ambiguity (e.g., false positives from homonyms), and rapidly evolving slang. Iterative feedback loops and contextual analysis are essential to improve accuracy and adapt to cultural and linguistic diversity in content moderation.