Wikipedia talk (gl)
This is the communication network of the Galician 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 =  8,097

Volume  m =  63,809

Unique edge count  m̿ =  23,279

Loop count  l =  3,955

Wedge count  s =  18,550,063

Claw count  z =  22,382,348,663

Cross count  x =  23,425,727,965,064

Triangle count  t =  22,837

Square count  q =  5,022,119

4Tour count  T_{4} =  114,416,978

Maximum degree  d_{max} =  5,815

Maximum outdegree  d^{+}_{max} =  5,815

Maximum indegree  d^{−}_{max} =  2,143

Average degree  d =  15.761 1

Fill  p =  0.000 355 072

Average edge multiplicity  m̃ =  2.741 05

Size of LCC  N =  7,920

Size of LSCC  N_{s} =  1,009

Relative size of LSCC  N^{r}_{s} =  0.124 614

Diameter  δ =  7

50Percentile effective diameter  δ_{0.5} =  2.121 48

90Percentile effective diameter  δ_{0.9} =  2.990 63

Median distance  δ_{M} =  3

Mean distance  δ_{m} =  2.652 91

Gini coefficient  G =  0.856 243

Balanced inequality ratio  P =  0.136 258

Outdegree balanced inequality ratio  P_{+} =  0.077 575 3

Indegree balanced inequality ratio  P_{−} =  0.209 422

Relative edge distribution entropy  H_{er} =  0.738 498

Power law exponent  γ =  2.251 76

Tail power law exponent  γ_{t} =  3.071 00

Tail power law exponent with p  γ_{3} =  3.071 00

pvalue  p =  0.000 00

Outdegree tail power law exponent with p  γ_{3,o} =  1.951 00

Outdegree pvalue  p_{o} =  0.000 00

Indegree tail power law exponent with p  γ_{3,i} =  3.201 00

Indegree pvalue  p_{i} =  0.000 00

Degree assortativity  ρ =  −0.359 948

Degree assortativity pvalue  p_{ρ} =  0.000 00

In/outdegree correlation  ρ^{±} =  +0.709 225

Clustering coefficient  c =  0.003 693 30

Directed clustering coefficient  c^{±} =  0.047 796 5

Spectral norm  α =  1,899.32

Operator 2norm  ν =  984.015

Cyclic eigenvalue  π =  916.311

Algebraic connectivity  a =  0.154 410

Spectral separation  λ_{1}[A] / λ_{2}[A] =  1.647 82

Reciprocity  y =  0.253 834

Nonbipartivity  b_{A} =  0.726 009

Normalized nonbipartivity  b_{N} =  0.064 314 9

Algebraic nonbipartivity  χ =  0.297 571

Spectral bipartite frustration  b_{K} =  0.014 311 8

Controllability  C =  7,045

Relative controllability  C_{r} =  0.870 075

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.
