Wikipedia talk (bn)
This is the communication network of the Bangla 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 =  83,803

Volume  m =  122,078

Unique edge count  m̿ =  99,789

Loop count  l =  7,810

Wedge count  s =  607,190,714

Claw count  z =  3,752,050,222,613

Cross count  x =  19,040,630,407,127,920

Triangle count  t =  14,552

Square count  q =  7,409,430

4Tour count  T_{4} =  2,488,232,542

Maximum degree  d_{max} =  21,778

Maximum outdegree  d^{+}_{max} =  21,746

Maximum indegree  d^{−}_{max} =  1,440

Average degree  d =  2.913 45

Fill  p =  1.420 90 × 10^{−5}

Average edge multiplicity  m̃ =  1.223 36

Size of LCC  N =  83,521

Size of LSCC  N_{s} =  700

Relative size of LSCC  N^{r}_{s} =  0.008 352 92

Diameter  δ =  7

50Percentile effective diameter  δ_{0.5} =  3.286 95

90Percentile effective diameter  δ_{0.9} =  4.085 39

Median distance  δ_{M} =  4

Mean distance  δ_{m} =  3.617 18

Gini coefficient  G =  0.650 115

Balanced inequality ratio  P =  0.253 993

Outdegree balanced inequality ratio  P_{+} =  0.046 879 9

Indegree balanced inequality ratio  P_{−} =  0.404 651

Relative edge distribution entropy  H_{er} =  0.676 965

Power law exponent  γ =  11.294 7

Tail power law exponent  γ_{t} =  3.531 00

Tail power law exponent with p  γ_{3} =  3.531 00

pvalue  p =  0.000 00

Outdegree tail power law exponent with p  γ_{3,o} =  1.491 00

Outdegree pvalue  p_{o} =  0.175 000

Indegree tail power law exponent with p  γ_{3,i} =  3.601 00

Indegree pvalue  p_{i} =  0.000 00

Degree assortativity  ρ =  −0.510 017

Degree assortativity pvalue  p_{ρ} =  0.000 00

In/outdegree correlation  ρ^{±} =  +0.566 989

Clustering coefficient  c =  7.189 83 × 10^{−5}

Directed clustering coefficient  c^{±} =  0.011 875 9

Spectral norm  α =  1,262.02

Operator 2norm  ν =  640.447

Cyclic eigenvalue  π =  616.099

Algebraic connectivity  a =  0.018 549 5

Spectral separation  λ_{1}[A] / λ_{2}[A] =  1.531 08

Reciprocity  y =  0.037 529 2

Nonbipartivity  b_{A} =  0.795 504

Normalized nonbipartivity  b_{N} =  0.011 150 6

Algebraic nonbipartivity  χ =  0.024 876 4

Spectral bipartite frustration  b_{K} =  0.002 638 66

Controllability  C =  82,034

Relative controllability  C_{r} =  0.978 891

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.
