Wikipedia talk (eu)
This is the communication network of the Basque Wikipedia. Nodes represent
users, and an edge from user A to user B denotes that user A wrote a message on
the talk page of user B at a certain timestamp.
Metadata
Statistics
Size  n =  40,993

Volume  m =  58,120

Unique edge count  m̿ =  46,524

Loop count  l =  2,423

Wedge count  s =  452,599,778

Claw count  z =  4,296,627,707,315

Cross count  x =  31,495,070,549,626,512

Triangle count  t =  4,163

Square count  q =  688,013

4Tour count  T_{4} =  1,815,993,208

Maximum degree  d_{max} =  29,480

Maximum outdegree  d^{+}_{max} =  29,478

Maximum indegree  d^{−}_{max} =  1,612

Average degree  d =  2.835 61

Fill  p =  2.768 58 × 10^{−5}

Average edge multiplicity  m̃ =  1.249 25

Size of LCC  N =  40,854

Size of LSCC  N_{s} =  617

Relative size of LSCC  N^{r}_{s} =  0.015 051 4

Diameter  δ =  7

50Percentile effective diameter  δ_{0.5} =  1.918 56

90Percentile effective diameter  δ_{0.9} =  3.734 08

Median distance  δ_{M} =  2

Mean distance  δ_{m} =  2.828 47

Gini coefficient  G =  0.643 616

Balanced inequality ratio  P =  0.259 196

Outdegree balanced inequality ratio  P_{+} =  0.059 446 0

Indegree balanced inequality ratio  P_{−} =  0.411 906

Relative edge distribution entropy  H_{er} =  0.640 929

Power law exponent  γ =  16.004 6

Tail power law exponent  γ_{t} =  3.951 00

Tail power law exponent with p  γ_{3} =  3.951 00

pvalue  p =  0.000 00

Outdegree tail power law exponent with p  γ_{3,o} =  2.081 00

Outdegree pvalue  p_{o} =  0.001 000 00

Indegree tail power law exponent with p  γ_{3,i} =  4.131 00

Indegree pvalue  p_{i} =  0.000 00

Degree assortativity  ρ =  −0.546 059

Degree assortativity pvalue  p_{ρ} =  0.000 00

Clustering coefficient  c =  2.759 39 × 10^{−5}

Directed clustering coefficient  c^{±} =  0.017 571 5

Spectral norm  α =  926.778

Operator 2norm  ν =  473.976

Cyclic eigenvalue  π =  452.904

Spectral separation  λ_{1}[A] / λ_{2}[A] =  2.178 13

Reciprocity  y =  0.050 920 0

Normalized nonbipartivity  b_{N} =  0.003 538 48

Algebraic nonbipartivity  χ =  0.007 430 54

Controllability  C =  40,135

Relative controllability  C_{r} =  0.979 070

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]

Jun Sun, Jérôme Kunegis, and Steffen Staab.
Predicting user roles in social networks using transfer learning with
feature transformation.
In Proc. ICDM Workshop on Data Min. in Netw., 2016.
