Eigenvector-like measures of centrality for asymmetric relations

By Phillip Bonacich, Paulette Lloyd. 2001

1,092 citations recorded by the source corpus.

Subfields: Sociology and Political Science, Statistical and Nonlinear Physics

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Citations in the corpus

A Critical Review of Centrality Measures in Social Networks (2010, background): “For a node x, the EC is therefore defined as (Bonacich and Lloyd 2001) referring to an eigenvector for the maximum eigenvalue 4 λ max (A) of the adjacency matrix A.”
Control Centrality and Hierarchical Structure in Complex Networks (2012, background): “ness centrality [22], eigenvector centrality [23,24], PageRank [25], hub centrality and authority centrality [26], routing centrality [27], and so on.”
Vital nodes identification in complex networks (2016, background): “(64) has exactly the same form as the well-known alpha centrality [99]: Cα = (I − αA)−1−→e .”
State of the aRt personality research: A tutorial on network analysis of personality data in R (2015, neutral): “Among the most prominent of those indices are eigenvector centrality (Bonacich, 1972, 2007), Bonacich power (Bonacich, 1987) and alpha centrality (Bonacich & Lloyd, 2001).”
Graph based anomaly detection and description: a survey (2014, background): “The node-level features include (in/out) degrees, centrality measures such as eigenvector [Bonacich and Lloyd, 2001], closeness [Noh and Rieger, 2004], and betweenness [Freeman, 1977] centralities, local clustering coefficient [Watts and Strogatz, 1998], radius [Kang et al., 2011c], degree…”
Social network analysis and the evaluation of leadership networks (2010, background): “Bonacich and Lloyd (2001) overview several advanced influence metrics and explain how most of them compute nearly the same thing.”
The Role of Network Resources in Market Entry: Commercial Banks' Entry into Investment Banking, 1991–1997 (2003, methodology): “3 The eigenvector measure may produce misleading status scores if it is used on an asymmetric network in which some actors are not the object of deferential relations from other actors (Bonacich and Lloyd, 2001).”
Study on centrality measures in social networks: a survey (2018, result): “An alternative measure was suggested by Bonacich and Lloyd (2001) that gives meaningful comparable results.”
A review on trust propagation and opinion dynamics in social networks and group decision making frameworks (2019, background): “The eigenvector centrality proposed by Bonacich and Lloyd [2] has been extensively adopted as a measure of the relative importance of an individual in a social inﬂuence network.”
A network analysis of the volatility of high dimensional financial series (2017, background): “Table 5 shows, for the two periods that were considered, the rankings of firms according to a measure of eigenvector centrality adapted to weighted directed networks (see Bonacich and Lloyd (2001)).”
The Importance of Industry Links in Merger Waves (2012, neutral): “Eigenvector centrality cannot always be applied to asymmetric adjacency matrices (Bonacich and Lloyd, 2001).”
A tutorial on modeling and analysis of dynamic social networks. Part I (2017, methodology): “This centrality measure is similar to the eigenvector centrality [103], which is defined as the left eigenvector of the conventional binary adjacency matrix of a graph instead of the “normalized” stochastic adjacency matrix.”
Measuring user influence on Twitter: A survey (2015, methodology): “A more recent web application is tweetStim-uli [130], 11 that allow us to rank local inﬂuencers , a concept that comes from Bakshy et al. [4].”
Network Analysis of World Trade using the BACI-CEPII Dataset (2014, positive): “See also Bonacich and Lloyd (2001) and Newman (2010) on this issue.”