TREC WT10g

Metadata

CodeWT
Internal nametrec-wt10g
NameTREC WT10g
Data sourcehttp://ir.dcs.gla.ac.uk/test_collections/access_to_data.html
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Category
Hyperlink network
Network formatUnipartite, directed
Edge typeUnweighted, no multiple edges
ReciprocalContains reciprocal edges
Directed cyclesContains directed cycles
LoopsDoes not contain loops

Statistics

Size n =1,601,787
Volume m =8,063,026
Loop count l =0
Wedge count s =4,375,162,265
Claw count z =17,206,337,249,825
Cross count x =84,325,207,721,815,904
Triangle count t =21,071,515
Square count q =12,596,865,743
4-Tour count T4 =118,288,933,500
Maximum degree dmax =25,663
Maximum outdegree d+max =25,604
Maximum indegree dmax =7,237
Average degree d =10.067 5
Fill p =3.142 60 × 10−6
Size of LCC N =1,458,316
Size of LSCC Ns =470,441
Relative size of LSCC Nrs =0.293 698
Diameter δ =112
50-Percentile effective diameter δ0.5 =7.911 05
90-Percentile effective diameter δ0.9 =11.104 7
Mean distance δm =8.703 68
Gini coefficient G =0.637 390
Balanced inequality ratio P =0.266 576
Outdegree balanced inequality ratio P+ =0.214 135
Indegree balanced inequality ratio P =0.304 024
Relative edge distribution entropy Her =0.912 734
Power law exponent γ =1.744 92
Tail power law exponent γt =2.231 00
Degree assortativity ρ =−0.057 003 6
Degree assortativity p-value pρ =0.000 00
In/outdegree correlation ρ± =+0.397 732
Clustering coefficient c =0.014 448 5
Spectral norm α =349.929
Operator 2-norm ν =336.756
Cyclic eigenvalue π =89.433 7
Algebraic connectivity a =0.000 162 332
Reciprocity y =0.343 240
Non-bipartivity bA =0.043 241 4
Normalized non-bipartivity bN =0.000 182 942
Spectral bipartite frustration bK =1.183 14 × 10−5

Plots

Degree distribution

Cumulative degree distribution

Lorenz curve

Spectral distribution of the adjacency matrix

Spectral distribution of the normalized adjacency matrix

Spectral distribution of the Laplacian

Spectral graph drawing based on the adjacency matrix

Spectral graph drawing based on the Laplacian

Spectral graph drawing based on the normalized adjacency matrix

Hop distribution

In/outdegree scatter plot

Clustering coefficient distribution

SynGraphy

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] Peter Bailey, Nick Craswell, and David Hawking. Engineering a multi-purpose test collection for Web retrieval experiments. Inf. Process. and Manag., 39(6):853–871, 2003.