Yahoo advertisers

These are adjacency data from phrases bidded for in Yahoo advertisements. Nodes in the network are words, and a directed edge denotes that two words occurred one after the other in a phrase. The network contains loops.

Metadata

CodeYD
Internal namelasagne-yahoo
NameYahoo advertisers
Data sourcehttp://amici.dsi.unifi.it/lasagne/?page_id=227
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Category
Lexical network
Node meaningWord
Edge meaningAdjacency
Network formatUnipartite, directed
Edge typeUnweighted, no multiple edges
ReciprocalContains reciprocal edges
Directed cyclesContains directed cycles
LoopsContains loops

Statistics

Size n =653,260
Volume m =2,931,708
Loop count l =2
Wedge count s =39,072,502,469
Claw count z =2,303,288,746,427,543
Cross count x =1.174 09 × 1020
Triangle count t =67,260
Square count q =395,269,117
4-Tour count T4 =159,458,026,208
Maximum degree dmax =224,825
Maximum outdegree d+max =413
Maximum indegree dmax =224,821
Average degree d =8.975 62
Size of LCC N =653,260
Size of LSCC Ns =2,754
Relative size of LSCC Nrs =0.004 215 78
Diameter δ =5
50-Percentile effective diameter δ0.5 =2.770 96
90-Percentile effective diameter δ0.9 =3.749 93
Median distance δM =3
Mean distance δm =3.237 15
Gini coefficient G =0.548 822
Balanced inequality ratio P =0.298 544
Outdegree balanced inequality ratio P+ =0.334 668
Indegree balanced inequality ratio P =0.193 101
Power law exponent γ =2.798 77
Tail power law exponent γt =2.611 00
Degree assortativity ρ =−0.081 463 3
Degree assortativity p-value pρ =0.000 00
In/outdegree correlation ρ± =−0.683 057
Clustering coefficient c =5.164 25 × 10−6
Directed clustering coefficient c± =0.012 244 3
Spectral norm α =474.580
Operator 2-norm ν =474.472
Cyclic eigenvalue π =2.643 58
Reciprocity y =6.139 77 × 10−6
Non-bipartivity bA =0.000 393 239
Normalized non-bipartivity bN =0.058 508 8
Algebraic non-bipartivity χ =0.715 120
Spectral bipartite frustration bK =0.019 918 4
Controllability C =462,648
Relative controllability Cr =0.708 214

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

Degree assortativity

Hop distribution

Delaunay graph drawing

In/outdegree scatter plot

Clustering coefficient distribution

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 ]