Live topic generation from event streams

Social platforms constantly record streams of heterogeneous data about human's activities, feelings, emotions and conversations opening a window to the world in real-time. Trends can be computed but making sense out of them is an extremely challenging task due to the heterogeneity of the data and its dynamics making often short-lived phenomena. We develop a framework which collects microposts shared on social platforms that contain media items as a result of a query, for example a trending event. It automatically creates different visual storyboards that reflect what users have shared about this particular event. More precisely it leverages on: (i) visual features from media items for near-deduplication, and (ii) textual features from status updates to interpret, cluster, and visualize media items. A screencast showing an example of these functionalities is published at: http://youtu.be/8iRiwz7cDYY while the prototype is publicly available at http://mediafinder.eurecom.fr.