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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