This research demonstrates how large language models can be effectively deployed to identify and combat hate speech on social media platforms, addressing a critical online security challenge.

Key Findings:

• GPT-3.5 Turbo shows promising capabilities in detecting and classifying hate speech on social media
• The model provides a scalable approach to content moderation that can adapt to evolving forms of harmful content
• Research addresses the growing need for automated methods to protect democratic discourse online
• Contributes to both security and linguistic analysis fields by examining harmful language patterns

Business Impact: This approach offers potential solutions for platforms struggling with content moderation at scale, helping to create safer digital spaces while protecting brand reputation and user communities.

HateGPT: Unleashing GPT-3.5 Turbo to Combat Hate Speech on X