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Table 1 Structural statistics of the real-world social networks: nodes (N), links (L), size of the LCC, size of the LCC as % with respect the total number of network nodes, average node degree \(\left\langle k \right\rangle\), diameter (D), transitivity (C), the edge density and the modularity (Q)

From: Modularity affects the robustness of scale-free model and real-world social networks under betweenness and degree-based node attack

Network N L LCC LCC (%) \(\left\langle k \right\rangle\) D C Density Q
TV Shows 3892 17,262 3892 100 4.4 20.0 0.443 0.00228 0.830
Politician 5908 41,729 5908 100 7.1 14.0 0.429 0.00239 0.815
Government 7057 89,455 7057 100 12.7 10.0 0.433 0.00358 0.614
Public Figures 11,565 67,114 11,565 100 5.8 15.0 0.215 0.00100 0.645
Athletes 13,866 86,858 13,866 100 6.3 11.0 0.303 0.00090 0.637
Company 14,113 52,310 14,113 100 3.7 15.0 0.287 0.00053 0.656
New sites 27,917 206,259 27,917 100 16.2 15.0 0.138 0.00052 0.529
Artist 50,515 819,306 50,515 100 7.4 11.0 0.295 0.00064 0.457
SP500_1 315 8706 315 100 27.6 6.0 0.511 0.08802 0.253
SP500_2 371 10,636 369 99 28.7 6.0 0.718 0.07748 0.373
NetScience 1589 2742 379 24 1.7 17.0 0.878 0.00109 0.954
Email 1005 16,064 986 98 16.0 7.0 0.450 0.01592 0.341
  1. To compute modularity Q, a clustering step was executed in priori using the popular fast-greedy modularity optimization algorithm (Clauset et al. 2004)