Being a major form of online innovation, social media platforms emerge, diffuse across large populations; while many of them fail the competition for users, and sometimes eventually disappear. In this paper, rich empirical patterns of spatial diffusion and churn are illustrated at an unprecedented scale and over the full life-cycle of a social media app. For the first time in the literature, we evaluate the spatial accuracy of a theory-driven network-based innovation diffusion model with empirical data. In order to improve the predictive power of contagion models at the local level, we combine the most recent empirical approaches of city science and geographical social networks in laying out the directions of model correction.