EU institution
This is the email communication network of a large, undisclosed European
institution. Nodes represent individual persons. Edges between two persons are
directed and denote that at least one email has been sent from one person to
the other. All edges are simple: Even if a person has sent multiple emails to
another person, the two persons will be connected only by a single edge in that
direction. Spam emails have been removed from the dataset.
Metadata
Statistics
Size  n =  265,214

Volume  m =  420,045

Loop count  l =  1,089

Wedge count  s =  195,288,557

Claw count  z =  250,257,426,117

Cross count  x =  330,517,523,039,094

Triangle count  t =  267,313

Square count  q =  18,421,946

4Tour count  T_{4} =  929,258,758

Maximum degree  d_{max} =  7,636

Maximum outdegree  d^{+}_{max} =  930

Maximum indegree  d^{−}_{max} =  7,631

Average degree  d =  3.167 59

Fill  p =  5.971 77 × 10^{−6}

Size of LCC  N =  224,832

Size of LSCC  N_{s} =  34,203

Relative size of LSCC  N^{r}_{s} =  0.128 964

Diameter  δ =  14

50Percentile effective diameter  δ_{0.5} =  3.549 11

90Percentile effective diameter  δ_{0.9} =  4.439 88

Median distance  δ_{M} =  4

Mean distance  δ_{m} =  4.080 16

Gini coefficient  G =  0.663 243

Balanced inequality ratio  P =  0.239 929

Outdegree balanced inequality ratio  P_{+} =  0.348 808

Indegree balanced inequality ratio  P_{−} =  0.152 931

Relative edge distribution entropy  H_{er} =  0.798 488

Power law exponent  γ =  6.649 66

Tail power law exponent  γ_{t} =  2.931 00

Tail power law exponent with p  γ_{3} =  2.931 00

pvalue  p =  0.000 00

Outdegree tail power law exponent with p  γ_{3,o} =  2.971 00

Outdegree pvalue  p_{o} =  0.000 00

Indegree tail power law exponent with p  γ_{3,i} =  2.661 00

Indegree pvalue  p_{i} =  0.000 00

Degree assortativity  ρ =  −0.178 125

Degree assortativity pvalue  p_{ρ} =  0.000 00

In/outdegree correlation  ρ^{±} =  +0.145 893

Clustering coefficient  c =  0.004 106 43

Directed clustering coefficient  c^{±} =  0.014 716 4

Spectral norm  α =  152.046

Operator 2norm  ν =  87.357 1

Cyclic eigenvalue  π =  69.932 3

Algebraic connectivity  a =  0.000 202 791

Spectral separation  λ_{1}[A] / λ_{2}[A] =  1.602 95

Reciprocity  y =  0.261 970

Nonbipartivity  b_{A} =  0.425 255

Normalized nonbipartivity  b_{N} =  9.817 48 × 10^{−5}

Algebraic nonbipartivity  χ =  0.000 196 327

Spectral bipartite frustration  b_{K} =  1.619 03 × 10^{−5}

Controllability  C =  245,791

Relative controllability  C_{r} =  0.926 765

Plots
Matrix decompositions plots
Downloads
References
[1]

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

[2]

Jure Leskovec, Jon Kleinberg, and Christos Faloutsos.
Graph evolution: Densification and shrinking diameters.
ACM Trans. Knowl. Discov. from Data, 1(1):1–40, 2007.
