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» Sampling Representative Users from Large Social Networks
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ASUNAM
2009
IEEE
13 years 5 months ago
Automatically Detecting Points of Interest and Social Networks from Tracking Positions of Avatars in a Virtual World
With hundreds of millions of users already today, virtual worlds will become an important factor in tomorrow's media landscape. In a virtual world, users are represented by s...
Frank Kappe, Bilal Zaka, Michael Steurer
COMSWARE
2008
IEEE
13 years 9 months ago
Extracting dense communities from telecom call graphs
Social networks refer to structures made of nodes that represent people or other entities embedded in a social context, and whose edges represent interaction between entities. Typi...
Vinayaka Pandit, Natwar Modani, Sougata Mukherjea,...
GI
2009
Springer
14 years 2 days ago
Deriving Taxonomies from Automatic Analysis of Group Membership Structure in Large Social Networks
: We develop a method to create taxonomies in large social networks solely based on users group membership information. We illustrate our technique using an example of the Flickr p...
Marc Egger, Kai Fischbach, Peter A. Gloor, Andre L...
CIKM
2008
Springer
13 years 9 months ago
Efficient sampling of information in social networks
As online social networking emerges, there has been increased interest to utilize the underlying social structure as well as the available social information to improve search. In...
Gautam Das, Nick Koudas, Manos Papagelis, Sushruth...
PAKDD
2010
ACM
222views Data Mining» more  PAKDD 2010»
14 years 7 days ago
Online Sampling of High Centrality Individuals in Social Networks
In this work, we investigate the use of online or “crawling” algorithms to sample large social networks in order to determine the most influential or important individuals wit...
Arun S. Maiya, Tanya Y. Berger-Wolf