Layers of Doubt: Typology of Temporal Uncertainty in Dynamic Diffusion Networks

Abstract

Investigating diffusion on dynamic networks has become an important problem, e.g., how misinformation spreads across social platforms or pathogens circulate across contact tracing networks. Uncertainty plays a major role: the exact time a contact takes place, whether the nodes existed, or if the diffusion took place may be unknown. However, it is unclear which types of uncertainty need to be shown so that appropriate visualizations can be designed. Therefore, we present a novel typology of temporal uncertainty in dynamic networks and their associated diffusion processes. Our paper systematizes where uncertainty can arise. It can be used to characterize user requirements for new visualizations, assess their appropriateness, and support the development of novel designs.