This research demonstrates how Large Language Models can transform social media data into actionable emergency response insights customized for different stakeholders.

• Automates analysis of social media posts during disasters and emergencies
• Aggregates and customizes critical information for specific stakeholders (police, EMS, firefighters)
• Enhances coordination between emergency response agencies
• Provides real-time, relevant intelligence during crisis situations

For security professionals, this approach offers a significant advancement in emergency management capabilities by enabling faster, more informed decision-making based on public information streams during critical situations.

Multi-Stakeholder Disaster Insights from Social Media Using Large Language Models