With the urbanization process worldwide, modeling the dynamics of people's activities in urban environments has become a crucial socioeconomic task. We present Urbanity, a novel system that leverages geo-tagged social media streams for modeling urban dynamics. Urbanity automatically discovers the spatial and temporal hotspots where people's activities concentrate; and captures the cross-modal correlations among location, time, and text by jointly mapping different units into the same latent space. With Urbanity, the end users are able to use flexible query schemes to retrieve different resources (e.g., POIs, hotspots, hours, activities) that meet their needs. Furthermore, Urbanity can handle continuous streams to update the learned model, thus revealing up-to-date patterns of urban activitiec 2017 Association for Computing Machinery.