Wikipedia talk (lv)
This is the communication network of the Latvian 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 = | 41,424
|
| Volume | m = | 73,900
|
| Unique edge count | m̿ = | 51,098
|
| Loop count | l = | 8,740
|
| Wedge count | s = | 649,358,980
|
| Claw count | z = | 7,621,516,311,302
|
| Cross count | x = | 68,032,007,206,512,256
|
| Triangle count | t = | 10,408
|
| Square count | q = | 5,154,202
|
| 4-Tour count | T4 = | 2,638,768,688
|
| Maximum degree | dmax = | 35,755
|
| Maximum outdegree | d+max = | 35,733
|
| Maximum indegree | d−max = | 2,220
|
| Average degree | d = | 3.567 98
|
| Fill | p = | 2.977 83 × 10−5
|
| Average edge multiplicity | m̃ = | 1.446 24
|
| Size of LCC | N = | 41,278
|
| Size of LSCC | Ns = | 510
|
| Relative size of LSCC | Nrs = | 0.012 311 7
|
| Diameter | δ = | 6
|
| 50-Percentile effective diameter | δ0.5 = | 1.662 40
|
| 90-Percentile effective diameter | δ0.9 = | 3.095 04
|
| Median distance | δM = | 2
|
| Mean distance | δm = | 2.355 89
|
| Gini coefficient | G = | 0.709 842
|
| Balanced inequality ratio | P = | 0.218 606
|
| Outdegree balanced inequality ratio | P+ = | 0.057 659 0
|
| Indegree balanced inequality ratio | P− = | 0.357 673
|
| Relative edge distribution entropy | Her = | 0.630 515
|
| Power law exponent | γ = | 9.150 63
|
| Tail power law exponent | γt = | 3.291 00
|
| Tail power law exponent with p | γ3 = | 3.291 00
|
| p-value | p = | 0.000 00
|
| Outdegree tail power law exponent with p | γ3,o = | 2.181 00
|
| Outdegree p-value | po = | 0.000 00
|
| Indegree tail power law exponent with p | γ3,i = | 3.381 00
|
| Indegree p-value | pi = | 0.000 00
|
| Degree assortativity | ρ = | −0.593 242
|
| Degree assortativity p-value | pρ = | 0.000 00
|
| In/outdegree correlation | ρ± = | +0.604 761
|
| Clustering coefficient | c = | 4.808 43 × 10−5
|
| Directed clustering coefficient | c± = | 0.019 684 1
|
| Spectral norm | α = | 1,931.81
|
| Operator 2-norm | ν = | 981.703
|
| Cyclic eigenvalue | π = | 943.056
|
| Algebraic connectivity | a = | 0.080 124 8
|
| Spectral separation | |λ1[A] / λ2[A]| = | 1.419 92
|
| Reciprocity | y = | 0.040 451 7
|
| Non-bipartivity | bA = | 0.902 004
|
| Normalized non-bipartivity | bN = | 0.011 472 6
|
| Algebraic non-bipartivity | χ = | 0.026 898 5
|
| Spectral bipartite frustration | bK = | 0.002 753 43
|
| Controllability | C = | 40,325
|
| Relative controllability | Cr = | 0.973 469
|
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 ‣
Buy Me a Coffee
