Wikipedia edits (tet)

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


Internal nameedit-tetwiki
NameWikipedia edits (tet)
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 =4,623
Left size n1 =1,215
Right size n2 =3,408
Volume m =53,419
Unique edge count m̿ =20,551
Wedge count s =3,368,229
Claw count z =550,734,106
Cross count x =86,239,115,893
Square count q =12,434,637
4-Tour count T4 =113,005,390
Maximum degree dmax =3,272
Maximum left degree d1max =3,272
Maximum right degree d2max =439
Average degree d =23.110 1
Average left degree d1 =43.966 3
Average right degree d2 =15.674 6
Fill p =0.004 963 15
Average edge multiplicity m̃ =2.599 34
Size of LCC N =4,143
Diameter δ =14
50-Percentile effective diameter δ0.5 =3.869 32
90-Percentile effective diameter δ0.9 =5.907 13
Median distance δM =4
Mean distance δm =4.485 05
Gini coefficient G =0.841 713
Balanced inequality ratio P =0.149 310
Left balanced inequality ratio P1 =0.081 731 2
Right balanced inequality ratio P2 =0.177 577
Relative edge distribution entropy Her =0.803 319
Power law exponent γ =2.119 99
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 =1.641 00
Left p-value p1 =0.001 000 00
Right tail power law exponent with p γ3,2 =1.731 00
Right p-value p2 =0.000 00
Degree assortativity ρ =−0.207 431
Degree assortativity p-value pρ =1.511 87 × 10−198
Spectral norm α =451.992
Algebraic connectivity a =0.034 992 1
Spectral separation 1[A] / λ2[A]| =1.085 87
Controllability C =2,975
Relative controllability Cr =0.648 431


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

Double Laplacian graph drawing

Delaunay graph drawing

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.