A Graph-theoretic perspective on centrality

By Stephen P. Borgatti, Martin G. Everett. Soc. Networks, 2006

1,606 citations recorded by the source corpus.

Subfields: Sociology and Political Science, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/378d40b9d1131b2d09f8669e348de0b8d7ed00be

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Citations in the corpus

When managers become leaders: The role of manager network centralities, social power, and followers' perception of leadership (2017, methodology): “From these data, we used UCINET to compute each leader’s in-degree centrality in the team advice network, defined as the total number of advice nominations that the formal leader received from team members (Borgatti & Everett, 2006).”
An empirical study of the Mexican banking system’s network and its implications for systemic risk (2012, neutral): “More recently, Borgatti and Everett (2006) rightfully state that the measures of centrality asses the involvement of the nodes on the walk structure of the network and propose four classes of network centrality measures.”
Centrality measure in graphs (2010, background): “A further comment may be made in view of Borgatti & Everett’s note [55] that “all of the [centrality] measures evaluate a node’s involvement in the walk structure of a network”.”
Casualties of Social Combat (2014, background): “There are multiple centrality measures, each emphasizing different structural properties (Borgatti and Everett 2006; Freeman 1979).”
Boardroom Centrality and Firm Performance (2013, background): “As noted by Borgatti (2005) and Borgatti and Everett (2006), to the extent these assumptions do not capture the true flow of information and resources across boardroom networks, the use of standard centrality measures may not be completely appropriate.”
Vital nodes identification in complex networks (2016, background): “ndent to the speciﬁc dynamical processes under consideration. The concept centrality was just proposed to answer the question that how to characterize a node’s importance according 3 to the structure [29, 30, 31, 32]. Generally speaking, a centrality measure assigns a real value to each node in the ”
On variants of shortest-path betweenness centrality and their generic computation (2008, methodology): “Another, more sophisticated variant also mentioned in Borgatti and Everett (2006) does not filter out paths of excessive length, but weighs all shortest Algorithm 4: k-Betweenness input: directed graph G = (V, E), length bound k output: k-betweenness for all v ∈ V (initialized to 0) for s ∈ V do…”
Network Properties Revealed through Matrix Functions (2010, background): “We refer the reader to [11, 62, 70] for further details and references.”
A Critical Review of Centrality Measures in Social Networks (2010, background): “Instead, some very different concepts and context-specific interpretations of the centrality of a node exist (Borgatti and Everett 2006, p. 467) that may result from different objectives for the use of CM.”
Betweenness Centrality in Some Classes of Graphs (2014, background): “Betweennes centrality [3, 4, 5, 8, 12] indicates the betweenness of a vertex in a network and it measures the extent to which a vertex lies on the shortest paths between pairs of other vertices.”
Social Networks and the Diffusion of User-Generated Content: Evidence from YouTube (2012, background): “The centrality measures a node's involvement in the cohesiveness of the network, promoting localized conformity (Borgatti and Everett 2006).”