Microscopic evolution of social networks Export

@inproceedings{leskovec08, abstract = {We present a detailed study of network evolution by analyzing four large online social networks with full temporal information about node and edge arrivals. For the first time at such a large scale, we study individual node arrival and edge creation processes that collectively lead to macroscopic properties of networks. Using a methodology based on the maximum-likelihood principle, we investigate a wide variety of network formation strategies, and show that edge locality plays a critical role in evolution of networks. Our findings supplement earlier network models based on the inherently non-local preferential attachment.}, address = {New York, NY, USA}, author = {Leskovec, Jure and Backstrom, Lars and Kumar, Ravi and Tomkins, Andrew}, booktitle = {KDD '08: Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining}, citeulike-article-id = {3352998}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1401890.1401948}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1401890.1401948}, doi = {10.1145/1401890.1401948}, isbn = {978-1-60558-193-4}, keywords = {attachment, flickr, linkedin, network, preferential, social, yahoo}, location = {Las Vegas, Nevada, USA}, pages = {462--470}, posted-at = {2009-07-08 12:22:21}, priority = {2}, publisher = {ACM}, title = {Microscopic evolution of social networks}, url = {http://dx.doi.org/10.1145/1401890.1401948}, year = {2008} }

TY - CONF ID - leskovec08 L3 - citeulike-article-id:3352998 N2 - We present a detailed study of network evolution by analyzing four large online social networks with full temporal information about node and edge arrivals. For the first time at such a large scale, we study individual node arrival and edge creation processes that collectively lead to macroscopic properties of networks. Using a methodology based on the maximum-likelihood principle, we investigate a wide variety of network formation strategies, and show that edge locality plays a critical role in evolution of networks. Our findings supplement earlier network models based on the inherently non-local preferential attachment. CY - Las Vegas, Nevada, USA SN - 978-1-60558-193-4 AD - New York, NY, USA EP - 470 TI - Microscopic evolution of social networks PB - ACM T2 - KDD '08: Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining SP - 462 KW - attachment KW - flickr KW - linkedin KW - network KW - preferential KW - social KW - yahoo AU - Leskovec, Jure AU - Backstrom, Lars AU - Kumar, Ravi AU - Tomkins, Andrew PY - 2008/// UR - http://dx.doi.org/10.1145/1401890.1401948 ER -