Online social networking sites like MySpace, Orkut, and Flickr are among the most popular sites on the Web and continue to experience dramatic growth in their user population. The popularity of these sites offers a unique opportunity to study the dynamics of social networks at scale. Having a proper understanding of how online social networks grow can provide insights into the network structure, allow predictions of future growth, and enable simulation of systems on networks of arbitrary size. However, to date, most empirical studies have focused on static network snapshots rather than growth dynamics.
%0 Conference Paper
%1 mislove08
%A Mislove, Alan
%A Koppula, Hema S.
%A Gummadi, Krishna P.
%A Druschel, Peter
%A Bhattacharjee, Bobby
%B WOSP '08: Proceedings of the first workshop on Online social networks
%C New York, NY, USA
%D 2008
%I ACM
%K attachment, communities, flickr, network, preferential
%P 25--30
%R 10.1145/1397735.1397742
%T Growth of the flickr social network
%U http://dx.doi.org/10.1145/1397735.1397742
%X Online social networking sites like MySpace, Orkut, and Flickr are among the most popular sites on the Web and continue to experience dramatic growth in their user population. The popularity of these sites offers a unique opportunity to study the dynamics of social networks at scale. Having a proper understanding of how online social networks grow can provide insights into the network structure, allow predictions of future growth, and enable simulation of systems on networks of arbitrary size. However, to date, most empirical studies have focused on static network snapshots rather than growth dynamics.
%@ 978-1-60558-182-8
@inproceedings{mislove08,
abstract = {Online social networking sites like MySpace, Orkut, and Flickr are among the most popular sites on the Web and continue to experience dramatic growth in their user population. The popularity of these sites offers a unique opportunity to study the dynamics of social networks at scale. Having a proper understanding of how online social networks grow can provide insights into the network structure, allow predictions of future growth, and enable simulation of systems on networks of arbitrary size. However, to date, most empirical studies have focused on static network snapshots rather than growth dynamics.},
added-at = {2009-09-24T14:55:30.000+0200},
address = {New York, NY, USA},
author = {Mislove, Alan and Koppula, Hema S. and Gummadi, Krishna P. and Druschel, Peter and Bhattacharjee, Bobby},
biburl = {https://www.bibsonomy.org/bibtex/2338b889c10c90f08a2c0348201fcdd58/andreacapocci},
booktitle = {WOSP '08: Proceedings of the first workshop on Online social networks},
citeulike-article-id = {3271250},
citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1397735.1397742},
citeulike-linkout-1 = {http://dx.doi.org/10.1145/1397735.1397742},
doi = {10.1145/1397735.1397742},
interhash = {91951b29d710a35acf478523b3234ab2},
intrahash = {338b889c10c90f08a2c0348201fcdd58},
isbn = {978-1-60558-182-8},
keywords = {attachment, communities, flickr, network, preferential},
location = {Seattle, WA, USA},
pages = {25--30},
posted-at = {2008-12-16 19:24:50},
priority = {2},
publisher = {ACM},
timestamp = {2009-09-24T14:55:34.000+0200},
title = {Growth of the flickr social network},
url = {http://dx.doi.org/10.1145/1397735.1397742},
year = 2008
}