This research presents a novel framework that leverages large language models to extract medication side effects from social media conversations and organize them into structured knowledge graphs.

• Creates a systematic approach to mine valuable patient experiences from unstructured social media data
• Applied to semaglutide (weight loss medication) using Reddit data
• Transforms noisy user reports into organized, actionable medical insights
• Compares findings with official FDA adverse event reporting system

This work demonstrates how AI can enhance pharmacovigilance by capturing real-world patient experiences that might not appear in clinical trials, helping healthcare professionals better understand medication effects in diverse populations.

Crowdsourcing-Based Knowledge Graph Construction for Drug Side Effects Using Large Language Models with an Application on Semaglutide