Wikipedia edits (ca)

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


Internal nameedit-cawiki
NameWikipedia edits (ca)
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 =1,433,726
Left size n1 =64,855
Right size n2 =1,368,871
Volume m =17,396,142
Unique edge count m̿ =8,451,753
Wedge count s =488,493,598,538
Claw count z =38,157,676,563,995,488
Cross count x =2.695 94 × 1021
Maximum degree dmax =993,676
Maximum left degree d1max =993,676
Maximum right degree d2max =53,479
Average degree d =24.267 0
Average left degree d1 =268.231
Average right degree d2 =12.708 4
Fill p =9.520 08 × 10−5
Average edge multiplicity m̃ =2.058 29
Size of LCC N =1,418,923
Diameter δ =12
50-Percentile effective diameter δ0.5 =3.376 58
90-Percentile effective diameter δ0.9 =3.911 58
Median distance δM =4
Mean distance δm =3.641 61
Gini coefficient G =0.847 526
Balanced inequality ratio P =0.165 528
Left balanced inequality ratio P1 =0.032 835 2
Right balanced inequality ratio P2 =0.228 127
Relative edge distribution entropy Her =0.712 477
Power law exponent γ =1.925 23
Tail power law exponent γt =3.111 00
Degree assortativity ρ =−0.123 088
Degree assortativity p-value pρ =0.000 00
Algebraic connectivity a =0.027 695 2
Spectral separation 1[A] / λ2[A]| =1.311 76
Controllability C =1,315,427
Relative controllability Cr =0.922 566


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

Edge weight/multiplicity distribution

Temporal distribution

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.