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Table 3 Topological information of synthetic & real graphs

From: Fast cluster-based computation of exact betweenness centrality in large graphs

 

Graph

n

m

\(d_{avg}\)

\(d_{max}\)

\(cc_{avg}\)

Synthetic

Barabási-albert

6250

6249

1.999

126

0.000

Barabási-albert

12,500

12,499

1.999

225

0.000

Barabási-albert

25,000

24,999

1.999

344

0.000

Barabási-albert

50,000

49,999

1.999

463

0.000

Barabási-albert

100,000

99,999

1.999

1138

0.000

Barabási-albert

200,000

199,999

1.999

676

0.000

Barabási-albert

400,000

399,999

1.999

1142

0.000

Barabási-albert

800,000

799,999

1.999

1587

0.000

Real

Web-webbase-2001 [34]

16,062

25,593

3.187

1679

0.224

Ego-twitter [35]

22,322

31,823

2.851

238

0.072

Internet [34]

124,651

193,620

3.107

151

0.062

lyon-road-network1

156,102

178,845

2.291

8

0.017

Email-euAll [36]

224,832

339,925

3.024

7636

0.079

  1. The names of the graphs are given in the first column, whereas the number of nodes and edges are given in the second and third columns. \(d_{avg}\) and \(d_{max}\) are the average and max degree, respectively. \(cc_{avg}\) is the average clustering coefficient
  2. 1This dataset was supplied by the French National Institute of Geographic Information (IGN). https://www.ign.fr