Wikipedia talk (el)
This is the communication network of the Greek 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 = | 40,254
|
| Volume | m = | 190,279
|
| Unique edge count | m̿ = | 77,390
|
| Loop count | l = | 26,135
|
| Wedge count | s = | 181,858,756
|
| Claw count | z = | 581,119,219,524
|
| Cross count | x = | 1,536,422,106,910,311
|
| Triangle count | t = | 53,432
|
| Square count | q = | 66,577,096
|
| 4-Tour count | T4 = | 1,260,190,222
|
| Maximum degree | dmax = | 23,615
|
| Maximum outdegree | d+max = | 23,614
|
| Maximum indegree | d−max = | 6,251
|
| Average degree | d = | 9.453 92
|
| Fill | p = | 4.776 03 × 10−5
|
| Average edge multiplicity | m̃ = | 2.458 70
|
| Size of LCC | N = | 39,667
|
| Size of LSCC | Ns = | 2,421
|
| Relative size of LSCC | Nrs = | 0.060 143 1
|
| Diameter | δ = | 8
|
| 50-Percentile effective diameter | δ0.5 = | 2.729 31
|
| 90-Percentile effective diameter | δ0.9 = | 3.726 31
|
| Median distance | δM = | 3
|
| Mean distance | δm = | 3.232 07
|
| Gini coefficient | G = | 0.841 997
|
| Balanced inequality ratio | P = | 0.153 645
|
| Outdegree balanced inequality ratio | P+ = | 0.075 005 6
|
| Indegree balanced inequality ratio | P− = | 0.239 065
|
| Relative edge distribution entropy | Her = | 0.718 771
|
| Power law exponent | γ = | 3.419 32
|
| Tail power law exponent | γt = | 3.341 00
|
| Tail power law exponent with p | γ3 = | 3.341 00
|
| p-value | p = | 0.000 00
|
| Outdegree tail power law exponent with p | γ3,o = | 1.661 00
|
| Outdegree p-value | po = | 0.432 000
|
| Indegree tail power law exponent with p | γ3,i = | 3.491 00
|
| Indegree p-value | pi = | 0.000 00
|
| Degree assortativity | ρ = | −0.385 175
|
| Degree assortativity p-value | pρ = | 0.000 00
|
| In/outdegree correlation | ρ± = | +0.673 621
|
| Clustering coefficient | c = | 0.000 881 431
|
| Directed clustering coefficient | c± = | 0.021 507 0
|
| Spectral norm | α = | 3,905.03
|
| Operator 2-norm | ν = | 2,030.64
|
| Cyclic eigenvalue | π = | 1,889.59
|
| Algebraic connectivity | a = | 0.094 910 9
|
| Spectral separation | |λ1[A] / λ2[A]| = | 1.283 82
|
| Reciprocity | y = | 0.173 601
|
| Non-bipartivity | bA = | 0.314 832
|
| Normalized non-bipartivity | bN = | 0.021 515 7
|
| Algebraic non-bipartivity | χ = | 0.049 156 6
|
| Spectral bipartite frustration | bK = | 0.003 406 57
|
| Controllability | C = | 37,016
|
| Relative controllability | Cr = | 0.919 561
|
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.
|
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