Bandingkan kaedah

	Pusat Darjah Berwajaran	Pusat Kesihatan Kekerabatan
Bidang	Analisis Rangkaian	Analisis Rangkaian
Keluarga	Machine learning	Machine learning
Tahun asal	2004	1950 (formalized 1979)
Pengasas	Barrat, A.; Barthélemy, M.; Pastor-Satorras, R.; Vespignani, A.	Bavelas, A.; formalized by Freeman, L. C.
Jenis	Centrality measure for weighted networks	Node-level centrality index
Sumber perintis	Barrat, A., Barthélemy, M., Pastor-Satorras, R., & Vespignani, A. (2004). The architecture of complex weighted networks. Proceedings of the National Academy of Sciences, 101(11), 3747–3752.	Freeman, L. C. (1979). Centrality in social networks: Conceptual clarification. Social Networks, 1(3), 215–239.
Alias	node strength, strength centrality, weighted node degree, WDC	closeness, farness-based centrality, geodesic closeness, normalized closeness centrality
Berkaitan	6	6
Ringkasan	Weighted degree centrality — also called node strength — extends the classic degree centrality measure to networks whose edges carry numeric weights. Instead of simply counting a node's connections, it sums the weights of all edges incident to that node, capturing both the volume and the intensity of a node's ties in a single, interpretable score.	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.