In graph theory, eigenvector centrality (also called eigencentrality or prestige score[1]) is a measure of the influence of a node in a connected network. Relative scores are assigned to all nodes in the network based on the concept that connections to high-scoring nodes contribute more to the score of the node in question than equal connections to low-scoring nodes. A high eigenvector score means that a node is connected to many nodes who themselves have high scores.[2][3]
Google's PageRank and the Katz centrality are variants of the eigenvector centrality.[4]
^Zaki, Mohammed J.; Meira, Wagner Jr. (2014). Data Mining and Analysis: Fundamental Concepts and Algorithms. Cambridge University Press. ISBN 9780521766333.
^M. E. J. Newman. "The mathematics of networks" (PDF). Retrieved 2006-11-09. {{cite journal}}: Cite journal requires |journal= (help)
^Christian F. A. Negre, Uriel N. Morzan, Heidi P. Hendrickson, Rhitankar Pal, George P. Lisi, J. Patrick Loria, Ivan Rivalta, Junming Ho, Victor S. Batista. (2018). "Eigenvector centrality for characterization of protein allosteric pathways". Proceedings of the National Academy of Sciences. 115 (52): E12201–E12208. arXiv:1706.02327. Bibcode:2018PNAS..11512201N. doi:10.1073/pnas.1810452115. PMC 6310864. PMID 30530700.{{cite journal}}: CS1 maint: multiple names: authors list (link)
^David Austin. "How Google Finds Your Needle in the Web's Haystack". AMS.
and 28 Related for: Eigenvector centrality information
In graph theory, eigenvectorcentrality (also called eigencentrality or prestige score) is a measure of the influence of a node in a connected network...
mining) to enrich the centrality measures in complex networks. This is illustrated with eigenvectorcentrality, calculating the centrality of each node through...
actors. It is similar to Google's PageRank and to the eigenvectorcentrality. Katz centrality computes the relative influence of a node within a network...
principal eigenvector of the graph is also referred to merely as the principal eigenvector. The principal eigenvector is used to measure the centrality of its...
(2010) Systemic Import Analysis (SIA) – Application of Entropic EigenvectorCentrality (EEC) Criterion for a Priori Ranking of Financial Institutions in...
the University of Granada. The SJR indicator is a variant of the eigenvectorcentrality measure used in network theory. Such measures establish the importance...
result in a higher Eigenfactor score. Eigenfactor is similar to Eigenvectorcentrality and PageRank. Originally Eigenfactor scores were measures of a journal's...
see the computation section below). Thus this is a variant of the eigenvectorcentrality measure used commonly in network analysis. Because of the large...
measures of centrality are degree centrality, closeness centrality, betweenness centrality, eigenvectorcentrality, and katz centrality. The objective...
his paper on scoring chess tournaments is the earliest use of eigenvectorcentrality. Landau taught at the University of Berlin from 1899 to 1909, after...
musician with the highest degree and PageRank centralities, and the second highest Eigenvectorcentrality, of all musicians of all time. Over his career...
different types of centrality, including but not limited to degree centrality, eigenvectorcentrality, and betweenness centrality, which may all result...
(2010) Systemic Import Analysis (SIA) – Application of Entropic EigenvectorCentrality (EEC) Criterion for a Priori Ranking of Financial Institutions in...
properties of the graph's adjacency matrix. It uses the eigenvalues and eigenvectors of the adjacency matrix to position nodes in a low-dimensional space...
autonomous systems was calculated based on their eigenvectorcentrality, which is a measure of how central to the network each autonomous system is. Graph...
the multilayer generalization of Bonacich's eigenvectorcentrality per node per layer. The overall eigenvector versatility is simply obtained by summing...
unconnected. Centrality: Influence measured by number of connections and distance from others with high centralityEigenvectorcentrality: How well connected...
{\displaystyle S^{*}} is the image similarity matrix. As matrices are used, eigenvectorcentrality will be the measure applied, with repeated multiplication of V R...
Giorgio; Melzi, Simone (September 2016). "Features Selection via EigenvectorCentrality" (PDF). NFmcp2016. Retrieved 12 November 2016. R. Kohavi and G....
the variance that each eigenvector represents can be calculated by dividing the eigenvalue corresponding to that eigenvector by the sum of all eigenvalues...
various contributors, having both a high-scoring eigenvectorcentrality and betweenness centrality. The analysis also determined that the Early English...
connectivity, node strength, betweenness centrality, eccentricity, nodal efficiency, and eigenvectorcentrality. Between degree of connectivity and node...
Lisi GP, Loria JP, Rivalta I, Ho J, Batista VS (December 2018). "Eigenvectorcentrality for characterization of protein allosteric pathways". Proceedings...
factor of whether or not the user will click a link. The normalized eigenvectorcentrality combined with random surfer model's assumption of random jumps created...
Explicit formulas for eigenvalues and eigenvectors of the second derivative with different boundary conditions are provided both for the continuous and...
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