Sammenlign metoder
Gjennomgå de valgte metodene side om side; rader som avviker, er uthevet.
| Generalized Blockmodeling× | Core-Periphery Analysis× | |
|---|---|---|
| Fagfelt | Sociology | Sociology |
| Familie | Process / pipeline | Process / pipeline |
| Opprinnelsesår≠ | 2005 | 2000 |
| Opphavsperson≠ | Patrick Doreian, Vladimir Batagelj & Anuška Ferligoj | Stephen Borgatti & Martin Everett |
| Type≠ | Direct optimization partition of a network into positions with typed blocks | Network partition into a dense core and a sparse periphery |
| Opprinnelig kilde≠ | Doreian, P., Batagelj, V., & Ferligoj, A. (2005). Generalized Blockmodeling. Cambridge University Press. ISBN: 978-0-521-84085-9 | Borgatti, S. P., & Everett, M. G. (2000). Models of core/periphery structures. Social Networks, 21(4), 375–395. DOI ↗ |
| Alias | generalized blockmodel, direct blockmodeling, pre-specified blockmodeling, Doreian-Batagelj-Ferligoj blockmodeling | core/periphery model, Borgatti-Everett core-periphery, core-periphery structure detection, coreness analysis |
| Relaterte | 5 | 5 |
| Sammendrag≠ | 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. | Core/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. |
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