Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2487788.2487924 | WWW (Companion Volume) |
Field | DocType | ISBN |
Storytelling,World Wide Web,Social media,Computer science,Multimedia | Conference | 978-1-4503-2038-2 |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vuk Milicic | 1 | 10 | 2.20 |
| Giuseppe Rizzo | 2 | 349 | 37.75 |
| José Luis Redondo García | 3 | 46 | 7.81 |
| Raphaël Troncy | 4 | 1064 | 102.16 |
| Thomas Steiner | 5 | 13 | 1.88 |