Computational Social Networks

Table 4 Brandes2007 clustering results for LFR nets of 10,000 and 100,000 nodes

From: Comparing the speed and accuracy of approaches to betweenness centrality approximation

#	10,000 nodes							100,000 nodes
	\(\mu\)	Samples = 200		Samples = 100		Samples = 50		\(\mu\)	Samples = 50		Samples = 25		Samples = 10
	\(\mu\)	%	s	%	s	%	s	\(\mu\)	%	s	%	s	%	s
1	0.01	100	966	100	534	100	290	0.001	100	4466	99	2139	18	1546
2	0.02	100	1581	100	826	99	450	0.003	98	7492	89	8732	5	2975
3	0.03	96	1880	100	952	87	543	0.005	84	17,841	13	10,764	5	2803
4	0.04	99	2030	97	1063	75	615	0.001	100	11,631	100	6250	100	3110
5	0.05	99	2103	99	1103	30	624	0.005	99	19,514	100	13,045	41	9615
6	0.10	89	2377	34	1253	6	639	0.010	99	44,355	92	29,556	9	14,153

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