Wikipedia edits (nah)

This is the bipartite edit network of the Nāhuatl Wikipedia. It contains users and pages from the Nāhuatl Wikipedia, connected by edit events. Each edge represents an edit. The dataset includes the timestamp of each edit.

Metadata

Codenah
Internal nameedit-nahwiki
NameWikipedia edits (nah)
Data sourcehttp://dumps.wikimedia.org/
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Category
Authorship network
Dataset timestamp 2017-10-20
Node meaningUser, article
Edge meaningEdit
Network formatBipartite, undirected
Edge typeUnweighted, multiple edges
Temporal data Edges are annotated with timestamps

Statistics

Size n =20,068
Left size n1 =1,446
Right size n2 =18,622
Volume m =336,603
Unique edge count m̿ =139,970
Wedge count s =232,944,084
Claw count z =389,178,226,286
Cross count x =567,243,643,648,460
Square count q =860,924,482
4-Tour count T4 =7,819,583,820
Maximum degree dmax =28,828
Maximum left degree d1max =28,828
Maximum right degree d2max =960
Average degree d =33.546 2
Average left degree d1 =232.782
Average right degree d2 =18.075 6
Fill p =0.005 198 05
Average edge multiplicity m̃ =2.404 82
Size of LCC N =19,210
Diameter δ =12
50-Percentile effective diameter δ0.5 =2.830 91
90-Percentile effective diameter δ0.9 =3.864 14
Median distance δM =3
Mean distance δm =3.107 58
Gini coefficient G =0.842 237
Balanced inequality ratio P =0.172 341
Left balanced inequality ratio P1 =0.046 185 0
Right balanced inequality ratio P2 =0.224 597
Relative edge distribution entropy Her =0.747 510
Power law exponent γ =1.840 09
Tail power law exponent γt =3.191 00
Tail power law exponent with p γ3 =3.191 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.641 00
Left p-value p1 =0.000 00
Right tail power law exponent with p γ3,2 =5.851 00
Right p-value p2 =0.000 00
Degree assortativity ρ =−0.282 589
Degree assortativity p-value pρ =0.000 00
Spectral norm α =1,366.77
Algebraic connectivity a =0.038 064 0

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

Zipf plot

Hop distribution

Delaunay graph drawing

Edge weight/multiplicity distribution

Temporal distribution

Temporal hop distribution

Diameter/density evolution

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] Wikimedia Foundation. Wikimedia downloads. http://dumps.wikimedia.org/, January 2010.