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• W2049607688 endingPage "90" @default.
• W2049607688 startingPage "88" @default.
• W2049607688 abstract "Social networks evolve over time, driven by the shared activities and affiliations of their members, by similarity of individuals' attributes, and by the closure of short network cycles. We analyzed a dynamic social network comprising 43,553 students, faculty, and staff at a large university, in which interactions between individuals are inferred from time-stamped e-mail headers recorded over one academic year and are matched with affiliations and attributes. We found that network evolution is dominated by a combination of effects arising from network topology itself and the organizational structure in which the network is embedded. In the absence of global perturbations, average network properties appear to approach an equilibrium state, whereas individual properties are unstable." @default.
• W2049607688 created "2016-06-24" @default.
• W2049607688 creator A5000679279 @default.
• W2049607688 creator A5066696247 @default.
• W2049607688 date "2006-01-06" @default.
• W2049607688 modified "2023-10-11" @default.
• W2049607688 title "Empirical Analysis of an Evolving Social Network" @default.
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• W2049607688 doi "https://doi.org/10.1126/science.1116869" @default.
• W2049607688 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/16400149" @default.
• W2049607688 hasPublicationYear "2006" @default.
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