We demonstrate GeoTopics, a system to explore geographical patterns of urban activity. The system collects publicly shared check-ins generated by Foursquare users, that reveal who spends time where, when, and on what type of activity. It then employs sparse probabilistic modeling techniques to learn associations between different regions of a city and multi-feature descriptions of urban activity. Through a web interface, users of the system can select a city of interest and explore visualizations that highlight how different types of activity are spatially and temporally distributed in the city. We discuss the opportunities that web data offer to understand urban activity and the challenges one faces in that task. We then describe our approach and the architecture of GeoTopics. Finally, we lay out the demonstration scenario.