Wikipedia talk (zh)
This is the communication network of the Chinese 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 = | 1,219,241
|
Volume | m = | 2,284,546
|
Unique edge count | m̿ = | 1,735,118
|
Wedge count | s = | 454,139,500,995
|
Claw count | z = | 137,646,405,415,475,008
|
Triangle count | t = | 1,266,904
|
Square count | q = | 6,675,967,773
|
4-Tour count | T4 = | 1,869,969,123,320
|
Maximum degree | dmax = | 937,210
|
Maximum outdegree | d+max = | 937,208
|
Maximum indegree | d−max = | 9,268
|
Average degree | d = | 3.747 49
|
Fill | p = | 1.167 21 × 10−6
|
Average edge multiplicity | m̃ = | 1.316 65
|
Size of LCC | N = | 1,217,365
|
Size of LSCC | Ns = | 10,831
|
Relative size of LSCC | Nrs = | 0.008 883 40
|
Diameter | δ = | 8
|
50-Percentile effective diameter | δ0.5 = | 1.822 08
|
90-Percentile effective diameter | δ0.9 = | 3.716 31
|
Median distance | δM = | 2
|
Mean distance | δm = | 2.742 44
|
Gini coefficient | G = | 0.713 955
|
Balanced inequality ratio | P = | 0.209 474
|
Outdegree balanced inequality ratio | P+ = | 0.044 899 5
|
Indegree balanced inequality ratio | P− = | 0.346 666
|
Relative edge distribution entropy | Her = | 0.637 871
|
Power law exponent | γ = | 6.217 44
|
Tail power law exponent | γt = | 2.861 00
|
Degree assortativity | ρ = | −0.420 015
|
Degree assortativity p-value | pρ = | 0.000 00
|
In/outdegree correlation | ρ± = | +0.545 043
|
Clustering coefficient | c = | 8.369 04 × 10−6
|
Directed clustering coefficient | c± = | 0.021 421 7
|
Spectral norm | α = | 4,652.72
|
Operator 2-norm | ν = | 3,132.92
|
Cyclic eigenvalue | π = | 2,323.87
|
Algebraic connectivity | a = | 0.037 007 8
|
Spectral separation | |λ1[A] / λ2[A]| = | 1.425 91
|
Reciprocity | y = | 0.044 536 5
|
Non-bipartivity | bA = | 0.352 994
|
Normalized non-bipartivity | bN = | 0.012 765 2
|
Algebraic non-bipartivity | χ = | 0.029 891 8
|
Spectral bipartite frustration | bK = | 0.002 671 72
|
Controllability | C = | 1,201,258
|
Relative controllability | Cr = | 0.985 251
|
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.
|