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Structure and evolution of online social networks
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Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining table of contents
Philadelphia, PA, USA
POSTER SESSION: Research track posters table of contents
Pages: 611 - 617  
Year of Publication: 2006
ISBN:1-59593-339-5
Authors
Ravi Kumar  Yahoo! Research, Sunnyvale, CA
Jasmine Novak  Yahoo! Research, Sunnyvale, CA
Andrew Tomkins  Yahoo! Research, Sunnyvale, CA
Sponsors
ACM: Association for Computing Machinery
SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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ABSTRACT

In this paper, we consider the evolution of structure within large online social networks. We present a series of measurements of two such networks, together comprising in excess of five million people and ten million friendship links, annotated with metadata capturing the time of every event in the life of the network. Our measurements expose a surprising segmentation of these networks into three regions: singletons who do not participate in the network; isolated communities which overwhelmingly display star structure; and a giant component anchored by a well-connected core region which persists even in the absence of stars.We present a simple model of network growth which captures these aspects of component structure. The model follows our experimental results, characterizing users as either passive members of the network; inviters who encourage offline friends and acquaintances to migrate online; and linkers who fully participate in the social evolution of the network.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  35
 
 

Collaborative Colleagues:
Ravi Kumar: colleagues
Jasmine Novak: colleagues
Andrew Tomkins: colleagues