Identifying sets of key players in a social network

By Stephen P. Borgatti. Computational and mathematical organization theory, 2006

1,268 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/10f2c743c85ccd9b14a289b6154af973df1ed96c

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In Management Science and Operations Research

In Statistical and Nonlinear Physics

Citations in the corpus

A Critical Review of Centrality Measures in Social Networks (2010, background): “Since these CM do not exhaustively solve the particular problems, Borgatti (2006) additionally developed new CM that are better suited for the studied issues .”
Social Networks and Causal Inference (2013, methodology): “…that have been proposed in the literature to choose central subjects in a group/network according to the integrative criterion, including the indegree centrality method (Valente and Pumpuang 2007), the eigenvector centrality method (Bonacich 2007), and the key players method (Borgatti 2006).”
SINCERA: A Pipeline for Single-Cell RNA-Seq Profiling Analysis (2015, methodology): “This concept has been applied to the analysis of node importance in terrorist and social networks [61,64], criminal networks [65], and food webs [66].”
Who's Who in Networks - Wanted: The Key Group (2008, background): “However, recently Everett and Borgatti (1999, 2005) proposed new measures of a network group centralities of degree, closeness, and betweenness to account for the fact that optimal selection of a set of k actors is quite different from selecting the k actors with the largest individual centralities.”
Study on centrality measures in social networks: a survey (2018, methodology): “To get over the limitations of Costenbader and Valente (2003) and Borgatti (2006), a computational approach was taken and robustness was examined for large sample of graphs.”
Graph models of habitat mosaics. (2009, background): “Borgatti (2006) has recently introduced the notion of key players in social networks.”
Vital nodes identification in complex networks (2016, methodology): “[223] proposed a so-called equal graph partitioning (EGP) strategy (see also an earlier work with a similar idea [224]), which performs significantly better than simply selecting the highestdegree or highest-betweenness nodes in fragmenting the network.”
A method for detecting modules in quantitative bipartite networks (2013, background): “…one-mode networks or, more precisely, one-mode projections of bipartite networks (Guimerà et al. , 2007; Martín González et al. , 2012; Thébault, 2013), while other approaches fo-52 cus on the identiﬁcation of crucial species through quantiﬁcations of their position in the network (Borgatti, 2006).”