Interactive exploration and understanding of contagion dynamics in networked populations

Modeling and simulation of contagion processes on networked populations are used to understand protests, social unrest, the spread of information, and virus and disease epidemics, among other phenomena. Network structure and attributes of vertices and edges are often useful in explaining contagion spreading processes. However, particularly for larger networks (e.g., those with hundreds of thousands or millions of vertices), reasoning about and making sense of contagion propagation results is difficult owing to the scale of these simulations. We present a web application called NEMO for assisting an analyst in understanding contagion processes and in establishing causality. It has several features to query and visualize networks, subnetworks, and their properties. In addition to explaining NEMO's features, we provide a real case study of the spread of Ebola on a 4-million-vertex social network of Liberia, Africa. We demonstrate how NEMO can be used to explore interactively networks to understand the reasons for the effectiveness of different interventions.