Manufacturing emails
This is the internal email communication network between employees of a
midsized manufacturing company. The network is directed and nodes represent
employees. The left node represents the sender and the right node represents
the recipient. Edges between two nodes are individual emails.
Metadata
Statistics
Size  n =  167

Volume  m =  82,927

Unique edge count  m̿ =  5,784

Loop count  l =  51

Wedge count  s =  206,233

Claw count  z =  31,304,118

Cross count  x =  1,296,647,327

Triangle count  t =  37,209

Square count  q =  1,622,683

4Tour count  T_{4} =  13,812,896

Maximum degree  d_{max} =  9,053

Maximum outdegree  d^{+}_{max} =  4,607

Maximum indegree  d^{−}_{max} =  4,446

Average degree  d =  993.138

Fill  p =  0.207 394

Average edge multiplicity  m̃ =  14.337 3

Size of LCC  N =  167

Size of LSCC  N_{s} =  126

Relative size of LSCC  N^{r}_{s} =  0.754 491

Diameter  δ =  5

50Percentile effective diameter  δ_{0.5} =  1.395 03

90Percentile effective diameter  δ_{0.9} =  2.246 15

Median distance  δ_{M} =  2

Mean distance  δ_{m} =  1.871 18

Gini coefficient  G =  0.619 320

Balanced inequality ratio  P =  0.267 754

Outdegree balanced inequality ratio  P_{+} =  0.272 589

Indegree balanced inequality ratio  P_{−} =  0.303 689

Relative edge distribution entropy  H_{er} =  0.925 588

Power law exponent  γ =  1.332 56

Tail power law exponent  γ_{t} =  4.201 00

Tail power law exponent with p  γ_{3} =  4.201 00

pvalue  p =  0.109 000

Outdegree tail power law exponent with p  γ_{3,o} =  3.641 00

Outdegree pvalue  p_{o} =  0.187 000

Indegree tail power law exponent with p  γ_{3,i} =  4.951 00

Indegree pvalue  p_{i} =  0.431 000

Degree assortativity  ρ =  −0.295 177

Degree assortativity pvalue  p_{ρ} =  7.833 28 × 10^{−131}

In/outdegree correlation  ρ^{±} =  +0.852 125

Clustering coefficient  c =  0.541 266

Directed clustering coefficient  c^{±} =  0.538 752

Spectral norm  α =  3,581.16

Operator 2norm  ν =  1,819.32

Cyclic eigenvalue  π =  1,772.47

Algebraic connectivity  a =  0.904 879

Spectral separation  λ_{1}[A] / λ_{2}[A] =  1.122 82

Reciprocity  y =  0.876 037

Nonbipartivity  b_{A} =  0.109 389

Normalized nonbipartivity  b_{N} =  0.286 679

Algebraic nonbipartivity  χ =  0.377 080

Spectral bipartite frustration  b_{K} =  0.002 421 27

Controllability  C =  28

Relative controllability  C_{r} =  0.167 665

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]

Radoslaw Michalski, Sebastian Palus, and Przemyslaw Kazienko.
Matching organizational structure and social network extracted from
email communication.
In Proc. Int. Conf. on Bus. Inf. Syst., pages 197–206, 2011.
