Flickr hypergroups

Negoescu, Radu-Andrei, Adams, Brett, Phung, Dinh, Venkatesh, Svetha and Gatica-Perez, Daniel 2009, Flickr hypergroups, in MM'09 : Proceedings of the 17th ACM Multimedia Conference, ACM, New York, N. Y., pp. 813-816.

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Title Flickr hypergroups
Author(s) Negoescu, Radu-Andrei
Adams, Brett
Phung, DinhORCID iD for Phung, Dinh
Venkatesh, SvethaORCID iD for Venkatesh, Svetha
Gatica-Perez, Daniel
Conference name ACM International Conference on Multimedia (17th : 2009 : Beijing, China)
Conference location Beijing, China
Conference dates 19-24 Oct. 2009
Title of proceedings MM'09 : Proceedings of the 17th ACM Multimedia Conference
Editor(s) [Unknown]
Publication date 2009
Conference series ACM International Conference on Multimedia
Start page 813
End page 816
Total pages 4
Publisher ACM
Place of publication New York, N. Y.
Keyword(s) Flickr
human factors
Summary The amount of multimedia content available online constantly increases, and this leads to problems for users who search for content or similar communities. Users in Flickr often self-organize in user communities through Flickr Groups. These groups are particularly interesting as they are a natural instantiation of the content + relations social media paradigm. We propose a novel approach to group searching through hypergroup discovery. Starting from roughly 11,000 Flickr groups' content and membership information, we create three different bag-of-word representations for groups, on which we learn probabilistic topic models. Finally, we cast the hypergroup discovery as a clustering problem that is solved via probabilistic affinity propagation. We show that hypergroups so found are generally consistent and can be described through topic-based and similarity-based measures. Our proposed solution could be relatively easily implemented as an application to enrich Flickr's traditional group search.
ISBN 9781605586083
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2009, ACM
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