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Online social networks: modeling and mining: invited talk
Source Web Search and Web Data Mining archive
Proceedings of the Second ACM International Conference on Web Search and Data Mining table of contents
Barcelona, Spain
SESSION: Invited talks table of contents
Pages 2-2  
Year of Publication: 2009
ISBN:978-1-60558-390-7
Author
Ravi Kumar  Yahoo! Research, Sunnyvale, CA
Sponsors
SIGMOD: ACM Special Interest Group on Management of Data
: Google
SIGIR: ACM Special Interest Group on Information Retrieval
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
: Yahoo! Research
Microsoft : Microsoft
: Nokia
SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
Publisher
ACM  New York, NY, USA
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ABSTRACT

Online social networks have become major and driving phenomena on the Web. In this talk, we will address key modeling and algorithmic questions related to large online social networks. From the modeling perspective, we raise the question of whether there is a generative model for network evolution. The availability of time-stamped data makes it possible to study this question at an extremely fine granularity. We exhibit a simple, natural model that leads to synthetic networks with properties similar to the online ones. From an algorithmic viewpoint, we focus on data mining challenges posed by the magnitude of data in these networks. In particular, we examine topics related to influence and correlation in user activities and compressibility of such networks.