Wikipedia talk (eo)
This is the communication network of the Esperanto 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 =  7,586

Volume  m =  47,070

Unique edge count  m̿ =  17,362

Loop count  l =  9,827

Wedge count  s =  6,334,328

Claw count  z =  3,412,850,433

Cross count  x =  1,415,995,053,128

Triangle count  t =  18,044

Square count  q =  2,062,111

4Tour count  T_{4} =  41,862,732

Maximum degree  d_{max} =  5,157

Maximum outdegree  d^{+}_{max} =  3,540

Maximum indegree  d^{−}_{max} =  2,380

Average degree  d =  12.409 7

Fill  p =  0.000 301 699

Average edge multiplicity  m̃ =  2.711 09

Size of LCC  N =  7,253

Size of LSCC  N_{s} =  822

Relative size of LSCC  N^{r}_{s} =  0.108 358

Diameter  δ =  8

50Percentile effective diameter  δ_{0.5} =  2.575 43

90Percentile effective diameter  δ_{0.9} =  3.630 51

Median distance  δ_{M} =  3

Mean distance  δ_{m} =  3.095 16

Gini coefficient  G =  0.865 440

Balanced inequality ratio  P =  0.132 813

Outdegree balanced inequality ratio  P_{+} =  0.102 549

Indegree balanced inequality ratio  P_{−} =  0.194 370

Relative edge distribution entropy  H_{er} =  0.758 358

Power law exponent  γ =  3.047 78

Tail power law exponent  γ_{t} =  2.031 00

Tail power law exponent with p  γ_{3} =  2.031 00

pvalue  p =  0.026 000 0

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

Outdegree pvalue  p_{o} =  0.000 00

Indegree tail power law exponent with p  γ_{3,i} =  2.211 00

Indegree pvalue  p_{i} =  0.196 000

Degree assortativity  ρ =  −0.423 923

Degree assortativity pvalue  p_{ρ} =  0.000 00

In/outdegree correlation  ρ^{±} =  +0.715 506

Clustering coefficient  c =  0.008 545 82

Directed clustering coefficient  c^{±} =  0.056 901 0

Spectral norm  α =  1,762.80

Operator 2norm  ν =  889.457

Cyclic eigenvalue  π =  871.028

Algebraic connectivity  a =  0.101 624

Spectral separation  λ_{1}[A] / λ_{2}[A] =  1.422 85

Reciprocity  y =  0.279 058

Nonbipartivity  b_{A} =  0.753 769

Normalized nonbipartivity  b_{N} =  0.056 411 3

Algebraic nonbipartivity  χ =  0.100 022

Spectral bipartite frustration  b_{K} =  0.005 931 62

Controllability  C =  6,049

Relative controllability  C_{r} =  0.797 390

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.
