An Agent-Based Model of Urgent Diffusion in Social Media

With the growth of the use of social media, information is exchanged faster than ever. Understanding this diffusion of information is critical to planning for time sensitive events and situations. However, most traditional models of diffusion do not work well in situations where outside events are occurring at almost the same rate as diffusion dynamics within the network. In this paper, we present two models that provide insight into urgent diffusion dynamics using agent-based modeling. We fit these models to data drawn from four major urgent diffusion events including: (1) the capture of Osama Bin Laden, (2) Hurricane Irene, (3) Hurricane Sandy, and (4) Election Night 2012. We show that in some cases social networks play a large role in the diffusion of information and in other cases they do not, and discuss the robustness of our models to a wider variety of urgent diffusion situations.