Compara mètodes

	Centralitat Dinàmica per Proximitat	Centralitat de pas
Camp	Anàlisi de xarxes	Anàlisi de xarxes
Família	Machine learning	Machine learning
Any d'origen	2010–2012	1977
Autor original	Tang, J. et al.; Holme, P. & Saramäki, J.	Freeman, L. C.
Tipus	Centrality measure for temporal networks	Centrality measure
Font seminal	Tang, J., Musolesi, M., Mascolo, C., Latora, V. & Nicosia, V. (2010). Analysing information flows and key mediators through temporal centrality metrics. Proceedings of the 3rd Workshop on Social Network Systems (SNS '10). ACM.	Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41.
Àlies	temporal closeness centrality, time-varying closeness centrality, evolving network closeness, dynamic CC	Freeman betweenness, BC, geodesic betweenness, shortest-path betweenness
Relacionats	5	6
Resum	Dynamic closeness centrality extends classic closeness centrality to temporal networks by computing shortest time-respecting paths — paths that traverse edges in chronological order — and averaging inverse distances across all time windows. It reveals which nodes are most efficiently reached within an evolving network, tracking how a node's centrality rises and falls as connections appear and disappear over time.	Betweenness centrality, formalized by Linton C. Freeman in 1977, measures how often a node lies on the shortest path connecting every other pair of nodes in a network. High-betweenness nodes act as bridges or brokers: removing them fragments the network into disconnected components more severely than removing any other nodes.