Wikipedia talk (oc)
This is the communication network of the Occitan 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 =  3,144

Volume  m =  11,059

Unique edge count  m̿ =  4,835

Loop count  l =  1,188

Wedge count  s =  1,961,710

Claw count  z =  1,089,006,133

Cross count  x =  436,063,783,229

Triangle count  t =  1,531

Square count  q =  60,501

4Tour count  T_{4} =  8,339,044

Maximum degree  d_{max} =  3,251

Maximum outdegree  d^{+}_{max} =  2,202

Maximum indegree  d^{−}_{max} =  1,049

Average degree  d =  7.034 99

Fill  p =  0.000 489 138

Average edge multiplicity  m̃ =  2.287 28

Size of LCC  N =  3,054

Size of LSCC  N_{s} =  283

Relative size of LSCC  N^{r}_{s} =  0.090 012 7

Diameter  δ =  6

50Percentile effective diameter  δ_{0.5} =  2.209 99

90Percentile effective diameter  δ_{0.9} =  2.952 51

Median distance  δ_{M} =  3

Mean distance  δ_{m} =  2.687 79

Gini coefficient  G =  0.828 848

Balanced inequality ratio  P =  0.148 657

Outdegree balanced inequality ratio  P_{+} =  0.101 637

Indegree balanced inequality ratio  P_{−} =  0.219 188

Relative edge distribution entropy  H_{er} =  0.720 240

Power law exponent  γ =  4.981 79

Tail power law exponent  γ_{t} =  2.621 00

Tail power law exponent with p  γ_{3} =  2.621 00

pvalue  p =  0.000 00

Outdegree tail power law exponent with p  γ_{3,o} =  2.141 00

Outdegree pvalue  p_{o} =  0.004 000 00

Indegree tail power law exponent with p  γ_{3,i} =  2.801 00

Indegree pvalue  p_{i} =  0.001 000 00

Degree assortativity  ρ =  −0.518 834

Degree assortativity pvalue  p_{ρ} =  0.000 00

In/outdegree correlation  ρ^{±} =  +0.664 161

Clustering coefficient  c =  0.002 341 32

Directed clustering coefficient  c^{±} =  0.013 204 6

Spectral norm  α =  684.900

Operator 2norm  ν =  418.607

Cyclic eigenvalue  π =  277.690

Algebraic connectivity  a =  0.226 624

Spectral separation  λ_{1}[A] / λ_{2}[A] =  1.623 01

Reciprocity  y =  0.228 128

Nonbipartivity  b_{A} =  0.597 879

Normalized nonbipartivity  b_{N} =  0.055 316 2

Algebraic nonbipartivity  χ =  0.125 065

Spectral bipartite frustration  b_{K} =  0.010 905 3

Controllability  C =  2,697

Relative controllability  C_{r} =  0.857 824

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.
