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Core-Periphery Analysis×Generalized Blockmodeling×
BidangSociologySociology
KeluargaProcess / pipelineProcess / pipeline
Tahun asal20002005
PengasasStephen Borgatti & Martin EverettPatrick Doreian, Vladimir Batagelj & Anuška Ferligoj
JenisNetwork partition into a dense core and a sparse peripheryDirect optimization partition of a network into positions with typed blocks
Sumber perintisBorgatti, S. P., & Everett, M. G. (2000). Models of core/periphery structures. Social Networks, 21(4), 375–395. DOI ↗Doreian, P., Batagelj, V., & Ferligoj, A. (2005). Generalized Blockmodeling. Cambridge University Press. ISBN: 978-0-521-84085-9
Aliascore/periphery model, Borgatti-Everett core-periphery, core-periphery structure detection, coreness analysisgeneralized blockmodel, direct blockmodeling, pre-specified blockmodeling, Doreian-Batagelj-Ferligoj blockmodeling
Berkaitan55
RingkasanCore/periphery analysis partitions a network into a densely interconnected core of actors and a sparse periphery whose members connect to the core but not to one another. Formalized by Borgatti and Everett, the method fits the observed adjacency matrix to an idealized block pattern — a fully connected core block, an empty periphery block, and core–periphery blocks of intermediate density — to test whether and how strongly a network exhibits this canonical mesoscale structure.Generalized blockmodeling, developed by Doreian, Batagelj, and Ferligoj, partitions the actors of a network into positions and simultaneously characterizes the ties between positions as one of several allowed block types — null, complete, regular, dominant, and others. Rather than the indirect, two-step approach of computing equivalences and then clustering, it directly searches for the partition that minimizes the inconsistency between the observed network and an idealized block structure, optionally one the analyst pre-specifies from theory.
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ScholarGateBandingkan kaedah: Core-Periphery Analysis · Generalized Blockmodeling. Dicapai 2026-06-24 daripada https://scholargate.app/ms/compare