Wikipedia edits (ang)

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


Internal nameedit-angwiki
NameWikipedia edits (ang)
Data source
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
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


Size n =16,202
Left size n1 =2,207
Right size n2 =13,995
Volume m =168,436
Unique edge count m̿ =75,013
Wedge count s =56,387,716
Claw count z =47,382,466,315
Cross count x =35,434,055,394,561
Square count q =135,379,384
4-Tour count T4 =1,308,789,770
Maximum degree dmax =11,785
Maximum left degree d1max =11,785
Maximum right degree d2max =729
Average degree d =20.792 0
Average left degree d1 =76.319 0
Average right degree d2 =12.035 4
Fill p =0.002 428 63
Average edge multiplicity m̃ =2.245 42
Size of LCC N =14,788
Diameter δ =15
50-Percentile effective diameter δ0.5 =3.271 57
90-Percentile effective diameter δ0.9 =3.991 71
Median distance δM =4
Mean distance δm =3.570 10
Gini coefficient G =0.857 025
Balanced inequality ratio P =0.148 626
Left balanced inequality ratio P1 =0.052 251 3
Right balanced inequality ratio P2 =0.183 714
Relative edge distribution entropy Her =0.763 423
Power law exponent γ =2.135 03
Tail power law exponent γt =1.741 00
Tail power law exponent with p γ3 =1.741 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.791 00
Left p-value p1 =0.000 00
Right tail power law exponent with p γ3,2 =1.741 00
Right p-value p2 =0.000 00
Degree assortativity ρ =−0.274 807
Degree assortativity p-value pρ =0.000 00
Spectral norm α =637.380
Spectral separation 1[A] / λ2[A]| =1.258 41
Controllability C =12,163
Relative controllability Cr =0.760 473


Fruchterman–Reingold graph drawing

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

Edge weight/multiplicity distribution

Temporal distribution

Temporal hop distribution

Diameter/density evolution

Matrix decompositions plots



[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., January 2010.