Wikipedia talk (nds)
This is the communication network of the Low 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 = | 23,132
|
| Volume | m = | 27,432
|
| Unique edge count | m̿ = | 24,668
|
| Loop count | l = | 1,525
|
| Wedge count | s = | 254,797,256
|
| Claw count | z = | 1,922,100,442,042
|
| Cross count | x = | 10,855,404,680,187,870
|
| Triangle count | t = | 739
|
| Square count | q = | 95,989
|
| 4-Tour count | T4 = | 1,020,005,236
|
| Maximum degree | dmax = | 22,612
|
| Maximum outdegree | d+max = | 22,563
|
| Maximum indegree | d−max = | 962
|
| Average degree | d = | 2.371 78
|
| Fill | p = | 4.610 07 × 10−5
|
| Average edge multiplicity | m̃ = | 1.112 05
|
| Size of LCC | N = | 23,050
|
| Size of LSCC | Ns = | 155
|
| Relative size of LSCC | Nrs = | 0.006 700 67
|
| Diameter | δ = | 6
|
| 50-Percentile effective diameter | δ0.5 = | 1.511 43
|
| 90-Percentile effective diameter | δ0.9 = | 1.920 69
|
| Median distance | δM = | 2
|
| Mean distance | δm = | 2.025 14
|
| Gini coefficient | G = | 0.576 368
|
| Balanced inequality ratio | P = | 0.295 130
|
| Outdegree balanced inequality ratio | P+ = | 0.044 036 2
|
| Indegree balanced inequality ratio | P− = | 0.454 579
|
| Relative edge distribution entropy | Her = | 0.595 034
|
| Power law exponent | γ = | 24.251 7
|
| Tail power law exponent | γt = | 4.461 00
|
| Tail power law exponent with p | γ3 = | 4.461 00
|
| p-value | p = | 0.000 00
|
| Outdegree tail power law exponent with p | γ3,o = | 2.401 00
|
| Outdegree p-value | po = | 0.000 00
|
| Indegree tail power law exponent with p | γ3,i = | 4.691 00
|
| Indegree p-value | pi = | 0.000 00
|
| Degree assortativity | ρ = | −0.879 405
|
| Degree assortativity p-value | pρ = | 0.000 00
|
| In/outdegree correlation | ρ± = | +0.546 548
|
| Clustering coefficient | c = | 8.701 04 × 10−6
|
| Directed clustering coefficient | c± = | 0.001 506 22
|
| Spectral norm | α = | 794.828
|
| Operator 2-norm | ν = | 402.071
|
| Cyclic eigenvalue | π = | 391.973
|
| Algebraic connectivity | a = | 0.238 550
|
| Spectral separation | |λ1[A] / λ2[A]| = | 1.886 61
|
| Reciprocity | y = | 0.025 012 2
|
| Non-bipartivity | bA = | 0.810 433
|
| Normalized non-bipartivity | bN = | 0.007 856 82
|
| Algebraic non-bipartivity | χ = | 0.017 531 0
|
| Spectral bipartite frustration | bK = | 0.002 062 78
|
| Controllability | C = | 22,641
|
| Relative controllability | Cr = | 0.978 774
|
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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