EXSED: An intelligent tool for exploration of social events dynamics from augmented trajectories

Abstract

The dynamics of social events happening in large metropolitan areas are extremely complex. Location-based user generated data could be an exceptionally rich source of information about events, however the vastness and the heterogeneity of such information makes it almost impossible for city managers to have a comprehensive view. Some events are planned and advertised only among restricted communities, for many it is problematic to estimate the number of attendees, and in general it is very difficult to have information about citizen mobility in areas nearby or where events happen. In this paper, we describe EXSED, an interactive intelligent tool to support the visual exploration of social events dynamics along the spatial, temporal and organizational dimensions. Major functionalities include: (i) studying events that are either officially/unofficially planned and with global/local scope, (ii) extract discussion topics for an event and investigate their temporal and spatial profile, (iii) estimate event attendees and correlate their mobility patterns with the event evolution. We present preliminary results of a field study with officials from Dublin City Council (Ireland), who evaluated our tool on real world user-generated tweeter data and events in the city. © 2013 IEEE.