Structure of growing social networks.

By Emily Jin, Michelle Girvan, Mark Newman. Physical review. E, Statistical, nonlinear, and soft matter physics, 2001

557 citations recorded by the source corpus.

Subfields: Sociology and Political Science, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/6dd7f7a8cc1999566b22355bd05c4675b2131a14

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In Sociology and Political Science

In Statistical and Nonlinear Physics

Citations in the corpus

Random graphs with clustering. (2009, background): “…of clustered networks have been proposed that are more general in scope, almost all based on some form of “triadic closure” process in which one searches an initially unclustered network for pairs of vertices with a common neighbor and then connects them to form tri-angles [9, 10, 11, 12, 13].”
Why social networks are different from other types of networks. (2003, unknown): “Several models of this “triadic closure” process have been studied in the literature [35, 36, 37, 38, 39, 40].”
Do People Mix at Mixers? Structure, Homophily, and the “Life of the Party” (2007, background): “…parties form a bridge along which information may travel and also provide social closure (contacts all know each other), which is comforting and facilitates social control and therefore trust (Van De Bunt, Van Duijn, and Snijders, 1999; Gulati and Gargiulo, 1999; Jin, Girvan, and Newman, 2001).”
A synaptic organizing principle for cortical neuronal groups (2011, background): “This common neighbor rule is reminiscent of the mutual acquaintance rule described for social networks (61) but without the typical hub-like arrangement.”
Structural Deep Network Embedding (2016, background): “Such an assumption has been proved reasonable in many ﬁelds [6, 14].”
Patterns and dynamics of users' behavior and interaction: Network analysis of an online community (2009, background): “As a few scholars have pointed out (e.g., Jin et al., 2001; Watts, 2004), when the cost for creating and maintaining additional social relationships or searching for new acquaintances prevents individuals from having a disproportionately large number of relationships with others, the degree…”
Statistical physics of social dynamics (2007, background): “These results opened the way to a modeling activity aimed at reproducing in an artificial and controlled way the same features observed in real social networks (Jin et al., 2001).”
The Matthew effect in empirical data (2014, background): “We also discuss whether the Matthew effect is due to chance or optimisation, for example related to homophily in social systems or efficacy in technological systems, and we outline possible directions for future research.”
The Structure and Function of Complex Networks (2003, background): “ct growth processes that might be taking place on the real networks, and it is these growthprocessesthatlead tothe characteristicstructural features of the network.28 For example, a number of authors [30, 102, 198, 217, 220, 242, 397, 398, 411, 412] have studied models of network transitivity that m”
Clustering and preferential attachment in growing networks. (2001, methodology): “This form appears to fit reasonably well and might be suitable for use in the models.”