Ahmad Subhi Zolkafly

Offensive Language Detection in Social Media Text Using N-Gram Features and Multinomial Naïve Bayes

Offensive language on social-media and messaging platforms creates a need for moderation methods that are accurate, fast, and transparent. This study evaluates a count-based n-gram and Multinomial Naïve Bayes pipeline for binary offensive-language detection and demonstrates its integration into a Telegram bot. The expe...