with during the event, ranked by the measured strengths of the interactions. On top of that, the system provides an interactive web-based visualization that allows users to browse their ego networks across all supported systems, exploring the interplay of face-to-face time, on-line friendships and shared interest. The system also provides simple forms of recommendation, by suggesting the closure of social triangles that span the supported networks: for example, if attendee A has spent face-to-face time with attendee B, the system can point her to the profile of a third attendee C who is a Facebook friend of both A and B, and hasn’t met A yet at the event.
Visualization of graph data is incredibly challenging, particularly when it comes to extremely large, scale-free graphs and social networks. A few simple searches on the Web and you will find some mesmerizing and very cool images. Perhaps the most cited...
The integration of sensors with social networks will lead to real-time data and more useful web apps. In recent posts we reviewed an MIT experiment called WikiCity, that gathered real-time location data from mobile phones in Rome and graphically mapped trends from it. We then looked at a more commercial product doing similar real-time location data analysis, called Citysense. That product aims to let users find the most popular night spots in San Francisco and the most efficient ways to get to them. The next stage of projects/products such as Wikicity and Citysense will be to enable users to social...
[updated with Tagommenders paper – thanks Shilad.] The organizers of the World Wide Web conference recently announced the list of accepted papers for this year’s event. In the Social Networks and Web 2.0 track (chaired by Elisa Bertino and Lada...
L. Rombout, M. Atzmueller, und M. Postma. Proc. Workshop on Affective Computing and Context Awareness in Ambient Intelligence, UPV, Valencia, Spain, (2018)