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
Live topic generation from event streams
WWW 2013, 22nd International World Wide Web Conference, Demos Track, May 13-17, 2013, Rio de Janeiro, Brazil
Type:
Poster / Demo
City:
Rio de Janeiro
Date:
2013-05-13
Department:
Data Science
Eurecom Ref:
3970
Copyright:
© ACM, 2013. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in WWW 2013, 22nd International World Wide Web Conference, Demos Track, May 13-17, 2013, Rio de Janeiro, Brazil http://dx.doi.org/10.1145/2487788.2487924
PERMALINK : https://www.eurecom.fr/publication/3970