LSFES: A Linguistic Structure Feature Extraction System for Hate Speech and Offensive Language Classification

The rise in online interactions has increased hate speech, making its distinction from offensive language a key challenge. This paper introduces a novel methodology that combines structured-based and learning-based approaches to enhance classification. Traditional and deep learning-based features fail to retain contextual and grammatical meaning. By analyzing 1,700 sentences using constituency parse trees, we identified structural templates for hate speech. An Open Information Extraction System was developed to automate feature extraction using heuristic algorithms. We developed a Linguistic Structure Features Extraction System (LSFES). Our methodology shows a high precision in classification compared to the baseline.