Dependency Centrality from Bipartite Social Networks.
This paper introduces dependency centrality, a node-level measure of structural leadership in bipartite networks. The measure builds on Zhou et al.'s (2007) flow-based method to transform bipartite data and captures additional information from the second mode that existing measures of centrality typ...
| Publicado en: | Connections (02261766) Vol. 34; no. 1/2; pp. 14 - 29 |
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| Formato: | Artículo |
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Paradigm Publishing Services
Dec2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=120484480&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 120484480 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 02261766 DA5 jtl: Connections (02261766) issn: 02261766 maglogo: N pubinfo: dt: Dec2014 vid: 34 iid: 1/2 pid: 35924 pub: Paradigm Publishing Services artinfo: ui: 120484480 10.17266/34.1.2 ppf: 14 ppct: 15 formats: fmt: @attributes: type: P size: 2.8MB tig: atl: Dependency Centrality from Bipartite Social Networks. aug: au: Gerdes, Luke M. affil: United States Military Academy, West Point, New York su: Social networks Social interaction Bipartite graphs Betweenness relations (Mathematics) Eigenvectors sug: subj: Social networks Social interaction Other Individual and Family Services Bipartite graphs Betweenness relations (Mathematics) Eigenvectors ab: This paper introduces dependency centrality, a node-level measure of structural leadership in bipartite networks. The measure builds on Zhou et al.'s (2007) flow-based method to transform bipartite data and captures additional information from the second mode that existing measures of centrality typically exclude. Three previously published bipartite networks serve as test cases to demonstrate the extent of correlation among node-level centrality rankings derived from dependency centrality and those derived from canonical centrality measures: degree, closeness, betweenness, and eigenvector. Ultimately, dependency centrality appears to offer a novel means to measure importance in bipartite networks depicting social interactions. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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