Computational Social Networks

Table 1 Benchmark networks and their properties

From: Efficiently identifying critical nodes in large complex networks

Network	Type	\| V \|	\| E \|	ρ	δ	ξ
Conmat [33]	Collaboration	23,133	93,439	0.264	15	0.134
Ego [34]	Social	4,039	88,234	0.519	8	0.064
Flight [35]	Transportation	2,939	15,677	0.255	14	0.051
Powergrid [36]	Power grid	4,941	6,594	0.103	46	0.003
Relativity [33]	Collaboration	5,242	14,484	0.630	17	0.659
Oclinks [37]	Social	1,899	13,838	0.057	8	−0.188

|V| and |E| are the number of vertices and edges, ρ is the global clustering coefficient, δ is the diameter, and ξ is the degree assortativity.

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