Wikipedia dynamic (simple)
This network shows the evolution of hyperlinks between articles of the Simple
English Wikipedia. The nodes represent articles. An edge indicates that a
hyperlink was added or removed depending on the edge weight (−1 for removal
or +1 for addition).
Metadata
Statistics
Size  n =  100,312

Volume  m =  1,627,472

Unique edge count  m̿ =  746,086

Wedge count  s =  320,147,664

Claw count  z =  422,387,316,406

Cross count  x =  834,653,587,495,453

Triangle count  t =  2,020,060

Square count  q =  278,060,062

4Tour count  T_{4} =  3,276,402,818

Maximum degree  d_{max} =  33,633

Maximum outdegree  d^{+}_{max} =  16,280

Maximum indegree  d^{−}_{max} =  17,353

Average degree  d =  32.448 2

Fill  p =  7.501 46 × 10^{−5}

Average edge multiplicity  m̃ =  2.181 35

Size of LCC  N =  99,636

Size of LSCC  N_{s} =  54,524

Relative size of LSCC  N^{r}_{s} =  0.543 544

Diameter  δ =  12

50Percentile effective diameter  δ_{0.5} =  3.274 16

90Percentile effective diameter  δ_{0.9} =  4.660 77

Mean distance  δ_{m} =  3.830 55

Gini coefficient  G =  0.695 197

Relative edge distribution entropy  H_{er} =  0.888 087

Power law exponent  γ =  1.596 15

Tail power law exponent  γ_{t} =  2.301 00

Degree assortativity  ρ =  −0.070 451 9

Degree assortativity pvalue  p_{ρ} =  0.000 00

In/outdegree correlation  ρ^{±} =  +0.418 469

Clustering coefficient  c =  0.018 929 3

Spectral norm  α =  199.284

Operator 2norm  ν =  147.945

Cyclic eigenvalue  π =  65.652 3

Algebraic connectivity  a =  0.047 159 5

Spectral separation  λ_{1}[A] / λ_{2}[A] =  1.342 24

Reciprocity  y =  0.126 581

Nonbipartivity  b_{A} =  0.260 291

Normalized nonbipartivity  b_{N} =  0.024 180 5

Spectral bipartite frustration  b_{K} =  0.000 833 824

Controllability  C =  49,186

Relative controllability  C_{r} =  0.493 197

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]

Julia Preusse, Jérôme Kunegis, Matthias Thimm, Thomas Gottron, and Steffen
Staab.
Structural dynamics of knowledge networks.
In Proc. Int. Conf. on Weblogs and Soc. Media, 2013.
