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Bayesovská analýza ego sítí×Analýza ego sítí×
OborAnalýza sítíAnalýza sítí
RodinaMachine learningProcess / pipeline
Rok vzniku2010s1992 (Burt); foundational measurement formalised by Marsden 2002
TvůrceVarious (Bayesian SNA tradition; Krivitsky, Kolaczyk, Handcock among key contributors)Ronald S. Burt (structural holes framework); Peter V. Marsden (egocentric measures)
TypProbabilistic network modelDescriptive / relational network analysis
Původní zdrojKrivitsky, P. N., & Kolaczyk, E. D. (2015). On the question of effective sample size in network modeling: An asymptotic inquiry. Statistical Science, 30(2), 184–198. DOI ↗Burt, R.S. (1992). Structural Holes: The Social Structure of Competition. Harvard University Press. ISBN: 9780674843714
Další názvyBayesian personal network analysis, Bayesian egocentric network analysis, probabilistic ego network modeling, Bayesian egonetpersonal network analysis, egocentric network analysis, Ego Ağı Analizi (Personal Network Analysis)
Příbuzné56
ShrnutíBayesian ego network analysis applies probabilistic inference to ego-centered (personal) network data, combining a likelihood model for the ego's local network with prior distributions over network parameters. The result is a full posterior distribution that quantifies uncertainty about structural features such as alter composition, tie density, and network size — rather than producing point estimates alone.Ego network analysis examines the personal network of a focal individual — the ego — by mapping their direct contacts (alters) and the ties those contacts share with one another. Formalised through Ronald Burt's structural holes framework (1992) and Marsden's egocentric measurement approach (2002), the method produces ego-level indicators such as network size, density, constraint, and brokerage role that reveal how each individual's social position shapes their access to information, resources, and influence.
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ScholarGatePorovnat metody: Bayesian Ego Network Analysis · Ego Network Analysis. Získáno 2026-06-17 z https://scholargate.app/cs/compare