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Statistics
Size  n =  15,763

Volume  m =  171,206

Loop count  l =  871

Wedge count  s =  133,820,601

Claw count  z =  354,444,098,866

Cross count  x =  878,284,318,865,620

Triangle count  t =  591,156

Square count  q =  196,281,177

4Tour count  T_{4} =  2,105,828,990

Maximum degree  d_{max} =  11,408

Maximum outdegree  d^{+}_{max} =  852

Maximum indegree  d^{−}_{max} =  11,397

Average degree  d =  21.722 5

Fill  p =  0.000 689 035

Size of LCC  N =  15,763

Size of LSCC  N_{s} =  12,354

Relative size of LSCC  N^{r}_{s} =  0.783 734

Diameter  δ =  7

50Percentile effective diameter  δ_{0.5} =  1.963 41

90Percentile effective diameter  δ_{0.9} =  2.933 81

Median distance  δ_{M} =  2

Mean distance  δ_{m} =  2.555 10

Gini coefficient  G =  0.636 260

Balanced inequality ratio  P =  0.273 939

Outdegree balanced inequality ratio  P_{+} =  0.350 718

Indegree balanced inequality ratio  P_{−} =  0.192 084

Relative edge distribution entropy  H_{er} =  0.879 364

Power law exponent  γ =  1.485 09

Tail power law exponent  γ_{t} =  2.681 00

Tail power law exponent with p  γ_{3} =  2.681 00

pvalue  p =  0.000 00

Outdegree tail power law exponent with p  γ_{3,o} =  3.181 00

Outdegree pvalue  p_{o} =  0.000 00

Indegree tail power law exponent with p  γ_{3,i} =  1.981 00

Indegree pvalue  p_{i} =  0.000 00

Degree assortativity  ρ =  −0.121 510

Degree assortativity pvalue  p_{ρ} =  0.000 00

In/outdegree correlation  ρ^{±} =  +0.527 265

Clustering coefficient  c =  0.013 252 6

Directed clustering coefficient  c^{±} =  0.393 768

Spectral norm  α =  178.018

Operator 2norm  ν =  162.422

Cyclic eigenvalue  π =  61.075 3

Algebraic connectivity  a =  0.009 382 19

Spectral separation  λ_{1}[A] / λ_{2}[A] =  1.198 67

Reciprocity  y =  0.259 167

Nonbipartivity  b_{A} =  0.165 743

Normalized nonbipartivity  b_{N} =  0.004 475 19

Algebraic nonbipartivity  χ =  0.008 923 82

Spectral bipartite frustration  b_{K} =  0.000 117 648

Controllability  C =  5,527

Relative controllability  C_{r} =  0.350 631

Plots
Matrix decompositions plots
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References
[1]

Jérôme Kunegis.
KONECT – The Koblenz Network Collection.
In Proc. Int. Conf. on World Wide Web Companion, pages
1343–1350, 2013.
[ http ]

[2]

Gergely Palla, Illés J. Farkas, Péter Pollner, Imre Derényi, and Tamás
Vicsek.
Directed network modules.
New J. Phys., 9(6):186, 2007.
