Wikipedia talk (br)
This is the communication network of the Breton 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 =  1,181

Volume  m =  13,754

Unique edge count  m̿ =  3,016

Loop count  l =  3,363

Wedge count  s =  196,495

Claw count  z =  18,620,328

Cross count  x =  1,255,334,749

Triangle count  t =  2,688

Square count  q =  99,938

4Tour count  T_{4} =  1,590,144

Maximum degree  d_{max} =  3,297

Maximum outdegree  d^{+}_{max} =  2,504

Maximum indegree  d^{−}_{max} =  1,418

Average degree  d =  23.292 1

Fill  p =  0.002 162 38

Average edge multiplicity  m̃ =  4.560 34

Size of LCC  N =  1,021

Size of LSCC  N_{s} =  146

Relative size of LSCC  N^{r}_{s} =  0.123 624

Diameter  δ =  8

50Percentile effective diameter  δ_{0.5} =  2.499 82

90Percentile effective diameter  δ_{0.9} =  3.716 44

Median distance  δ_{M} =  3

Mean distance  δ_{m} =  3.029 72

Gini coefficient  G =  0.893 481

Balanced inequality ratio  P =  0.106 224

Outdegree balanced inequality ratio  P_{+} =  0.096 917 3

Indegree balanced inequality ratio  P_{−} =  0.139 232

Relative edge distribution entropy  H_{er} =  0.800 928

Power law exponent  γ =  2.516 16

Tail power law exponent  γ_{t} =  2.411 00

Tail power law exponent with p  γ_{3} =  2.411 00

pvalue  p =  0.000 00

Outdegree tail power law exponent with p  γ_{3,o} =  2.011 00

Outdegree pvalue  p_{o} =  0.260 000

Indegree tail power law exponent with p  γ_{3,i} =  2.611 00

Indegree pvalue  p_{i} =  0.018 000 0

Degree assortativity  ρ =  −0.486 059

Degree assortativity pvalue  p_{ρ} =  5.881 53 × 10^{−275}

In/outdegree correlation  ρ^{±} =  +0.640 704

Clustering coefficient  c =  0.041 039 2

Directed clustering coefficient  c^{±} =  0.128 357

Spectral norm  α =  1,597.83

Operator 2norm  ν =  841.843

Cyclic eigenvalue  π =  747.668

Algebraic connectivity  a =  0.115 155

Spectral separation  λ_{1}[A] / λ_{2}[A] =  1.477 97

Reciprocity  y =  0.334 881

Nonbipartivity  b_{A} =  0.822 255

Normalized nonbipartivity  b_{N} =  0.080 055 5

Algebraic nonbipartivity  χ =  0.196 562

Spectral bipartite frustration  b_{K} =  0.009 903 76

Controllability  C =  759

Relative controllability  C_{r} =  0.642 676

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.
