Bandingkan kaedah

	Pusat Darjah Temporal	Pusat Darjah
Bidang	Analisis Rangkaian	Analisis Rangkaian
Keluarga	Machine learning	Machine learning
Tahun asal	2011–2012	1978
Pengasas	Holme, P.; Saramaki, J.; Kim, H.; Anderson, R.	Freeman, L. C.
Jenis	Centrality measure (temporal extension)	Node-level centrality measure
Sumber perintis	Holme, P. & Saramaki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125.	Freeman, L. C. (1978). Centrality in social networks: Conceptual clarification. Social Networks, 1(3), 215–239.
Alias	time-varying degree centrality, dynamic degree centrality, temporal node degree, TDC	node degree, degree score, DC, connectivity centrality
Berkaitan	6	6
Ringkasan	Temporal degree centrality extends the classic degree centrality to time-varying networks by counting how many distinct contacts a node accumulates over time. Rather than collapsing a dynamic network into a single static graph, it preserves the temporal order of edges, yielding a more faithful measure of a node's activity and reachability across the observation window.	Degree centrality is the simplest and most intuitive measure of a node's importance in a network, defined as the number of direct ties a node has to other nodes. Normalized by dividing by the maximum possible ties, it allows comparison across networks of different sizes and is the starting point of almost every network analysis.