Módszerek összehasonlítása

	A fokszám-központiság (Degree Centrality)	Modularity Analysis
Tudományterület	Hálózatelemzés	Hálózatelemzés
Módszercsalád	Machine learning	Machine learning
Keletkezés éve	1978	2004
Megalkotó	Freeman, L. C.	Newman, M. E. J. & Girvan, M.
Típus	Node-level centrality measure	Community detection / graph partitioning
Alapmű	Freeman, L. C. (1978). Centrality in social networks: Conceptual clarification. Social Networks, 1(3), 215–239.	Newman, M. E. J., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69(2), 026113.
Alternatív nevek	node degree, degree score, DC, connectivity centrality	Q-modularity, community structure detection, network modularity optimization, graph partitioning by modularity
Kapcsolódó	6	5
Összefoglaló	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.	Modularity analysis is a network science method, formalized by Newman and Girvan in 2004, that detects community structure in graphs by measuring whether edges are more concentrated within groups than expected by chance. Its scalar quality index Q guides algorithms that partition nodes into cohesive clusters, making it the most widely adopted framework for community detection in social, biological, and technological networks.