Understanding human mobility during events in foursquare

Social events can generate high influxes of people transitioning various locations in a city. They can be considered to have a considerable impact on the local economy, whether they are sport events, concerts or festivals. These events are capable of generating sudden changes in the activity landscape of a city, with the neighborhoods that host events becoming unusually busy and active compared to times of regular citizen activity. While event and anomaly detection more generally has been a topic of study in recent years, as also has been event recommendation for mobile users, progress has been slower towards building systems that are able to capture the sudden shift appropriately in this setting. In this work we exploit data from the location-based service Foursquare to study mobility during events in Chicago, and later expand our study to other cities as well. Our aim is to identify what differences emerge in terms of user mobility during events versus regular periods of human activity.