This research introduces a novel epidemiology-informed framework for detecting rumors on social media by treating misinformation spread like disease propagation.

• Leverages graph neural networks to capture information propagation patterns beyond text-only solutions
• Incorporates epidemic modeling principles to understand how different rumors spread through networks
• Achieves superior performance by accounting for varying outreach capabilities of different source information
• Provides a more robust detection system that adapts to the network characteristics of misinformation

This innovation matters for security professionals by offering more reliable tools to maintain information integrity and public trust in digital spaces, helping to combat the growing threat of targeted misinformation campaigns.

Epidemiology-informed Network for Robust Rumor Detection