Σύγκριση μεθόδων

	Ανάλυση Κεντρικότητας	Μοντέλο Στοχαστικών Τμημάτων
Πεδίο	Ανάλυση Δικτύων	Ανάλυση Δικτύων
Οικογένεια	Process / pipeline	Process / pipeline
Έτος προέλευσης	1979	1983
Δημιουργός	Linton C. Freeman	—
Τύπος	Descriptive / exploratory network measure family	Probabilistic generative graph model
Θεμελιώδης πηγή	Freeman, L.C. (1979). Centrality in Social Networks: Conceptual Clarification. Social Networks, 1(3), 215-239.	Holland, P.W., Laskey, K.B. & Leinhardt, S. (1983). Stochastic Blockmodels: First Steps. Social Networks, 5(2), 109-137.
Εναλλακτικές ονομασίες	Merkeziyet Analizi (Degree, Betweenness, Eigenvector), node centrality, centrality measures, graph centrality	SBM, degree-corrected SBM, DCSBM, Stokastik Blok Modeli (SBM)
Συναφείς	5	7
Σύνοψη	Centrality analysis is a family of network-analytic measures, formalized by Freeman (1979), that quantifies the structural importance of individual nodes within a graph. Each centrality index captures a distinct mechanism of influence: degree centrality reflects direct connectivity, betweenness centrality identifies nodes that broker information flow, closeness centrality captures proximity to all others, and eigenvector centrality (along with PageRank) rewards connection to highly connected neighbors.	The Stochastic Block Model (SBM), introduced by Holland, Laskey and Leinhardt (1983), is a probabilistic generative model for graphs that assigns nodes to latent blocks and parametrically estimates the connection probabilities between blocks. It is the foundational approach for community detection, core-periphery identification, and hierarchical structure discovery in network analysis.