Порівняння методів

	Центральність власного вектора	Центральність за близькістю
Галузь	Мережевий аналіз	Мережевий аналіз
Родина	Machine learning	Machine learning
Рік появи	1972	1950 (formalized 1979)
Автор методу	Bonacich, P.	Bavelas, A.; formalized by Freeman, L. C.
Тип	Centrality measure	Node-level centrality index
Основоположне джерело	Bonacich, P. (1972). Factoring and weighting approaches to status scores and clique identification. Journal of Mathematical Sociology, 2(1), 113–120.	Freeman, L. C. (1979). Centrality in social networks: Conceptual clarification. Social Networks, 1(3), 215–239.
Інші назви	eigenvector centrality, EC, Bonacich centrality, power centrality	closeness, farness-based centrality, geodesic closeness, normalized closeness centrality
Пов'язані	6	6
Підсумок	Eigenvector centrality, introduced by Bonacich in 1972, measures a node's influence by considering not just how many neighbors it has, but how influential those neighbors are. A node scores highly if it is connected to other high-scoring nodes, making it a recursive, globally-aware measure of structural importance in a network.	Closeness centrality measures how quickly a node can reach all others in a network by computing the inverse of its average shortest-path distance to every other node. First described by Bavelas (1950) and formally unified by Freeman (1979), it identifies nodes that can spread information or resources efficiently across the entire graph — not merely nodes with many direct contacts.