Hadhari (حذارِ) - Arabic Spam Detection

Model Details

• Algorithm: Linear Support Vector Classification (LinearSVC)
• Feature Extraction: TF-IDF Vectorization (max_features=2000, ngram_range=(1,3))

Dataset

• Size: ~1000 unique messages
• Distribution: Balanced between genuine conversations and student-targeted spam.
• Characteristics: Contains real-world Saudi colloquial Arabic, slang, emojis, and common local spam patterns.

Example Data

Performance Metrics

• Overall Accuracy: 97.0%
• Spam Precision: 99.0%

Usage