Wikipedia talk (de)
This is the communication network of the German 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 = | 519,403
|
| Volume | m = | 6,729,794
|
| Unique edge count | m̿ = | 1,751,343
|
| Loop count | l = | 2,174,035
|
| Wedge count | s = | 22,215,138,984
|
| Claw count | z = | 983,926,400,524,723
|
| Cross count | x = | 3.502 66 × 1019
|
| Triangle count | t = | 9,554,210
|
| Square count | q = | 12,355,986,906
|
| 4-Tour count | T4 = | 187,711,464,036
|
| Maximum degree | dmax = | 395,780
|
| Maximum outdegree | d+max = | 395,774
|
| Maximum indegree | d−max = | 27,165
|
| Average degree | d = | 25.913 6
|
| Fill | p = | 6.491 76 × 10−6
|
| Average edge multiplicity | m̃ = | 3.842 65
|
| Size of LCC | N = | 505,468
|
| Size of LSCC | Ns = | 69,121
|
| Relative size of LSCC | Nrs = | 0.133 078
|
| Diameter | δ = | 13
|
| 50-Percentile effective diameter | δ0.5 = | 2.780 91
|
| 90-Percentile effective diameter | δ0.9 = | 3.746 41
|
| Median distance | δM = | 3
|
| Mean distance | δm = | 3.296 97
|
| Gini coefficient | G = | 0.916 814
|
| Balanced inequality ratio | P = | 0.092 355 7
|
| Outdegree balanced inequality ratio | P+ = | 0.076 872 0
|
| Indegree balanced inequality ratio | P− = | 0.137 522
|
| Relative edge distribution entropy | Her = | 0.763 449
|
| Power law exponent | γ = | 2.554 68
|
| Tail power law exponent | γt = | 1.811 00
|
| Tail power law exponent with p | γ3 = | 1.811 00
|
| p-value | p = | 0.000 00
|
| Outdegree tail power law exponent with p | γ3,o = | 1.741 00
|
| Outdegree p-value | po = | 0.000 00
|
| Indegree tail power law exponent with p | γ3,i = | 1.951 00
|
| Indegree p-value | pi = | 0.000 00
|
| Degree assortativity | ρ = | −0.124 769
|
| Degree assortativity p-value | pρ = | 0.000 00
|
| In/outdegree correlation | ρ± = | +0.723 786
|
| Clustering coefficient | c = | 0.001 290 23
|
| Directed clustering coefficient | c± = | 0.034 430 7
|
| Spectral norm | α = | 22,742.4
|
| Operator 2-norm | ν = | 18,161.3
|
| Cyclic eigenvalue | π = | 10,171.3
|
| Algebraic connectivity | a = | 0.033 983 0
|
| Spectral separation | |λ1[A] / λ2[A]| = | 1.117 23
|
| Reciprocity | y = | 0.223 920
|
| Non-bipartivity | bA = | 0.342 587
|
| Normalized non-bipartivity | bN = | 0.018 009 7
|
| Algebraic non-bipartivity | χ = | 0.033 969 5
|
| Spectral bipartite frustration | bK = | 0.001 349 57
|
| Controllability | C = | 413,087
|
| Relative controllability | Cr = | 0.795 311
|
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.
|
KONECT ‣ Networks ‣
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