Computational Social Networks

Table 7 Bader2007 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 = 250		Samples = 100		Samples = 50		\(\mu\)	Samples = 100		Samples = 50		Samples = 25
	\(\mu\)	%	s	%	s	%	s	\(\mu\)	%	s	%	s	%	s
1	0.01	100	630	100	281	100	171	0.001	96	5207	100	2534	100	1118
2	0.02	99	966	100	416	100	543	0.003	100	5677	99	4586	47	5752
3	0.03	97	1096	100	478	90	301	0.005	99	9749	86	12,131	12	7257
4	0.04	100	1185	100	522	14	319	0.001	100	12,385	100	8090	98	4644
5	0.05	96	1211	89	546	13	321	0.005	100	11,981	100	13,019	100	9446
6	0.10	93	1338	18	588	5	329	0.010	100	44,050	99	31,517	36	22,066

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