CiteULike user–item

This is the bipartite network of users and publications in CiteULike. Each edge represents a tag assignment that connects a users and a publication. Since a user can be assign multiple tags to a publication, the network contains multiple edges. The edges are annotated with the creation time of the tag assignment.


Internal nameciteulike-ui
NameCiteULike user–item
Data source
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Interaction network
Dataset timestamp 2007
Node meaningUser, publication
Edge meaningTag assignment
Network formatBipartite, undirected
Edge typeUnweighted, multiple edges
Temporal data Edges are annotated with timestamps


Size n =754,484
Left size n1 =22,715
Right size n2 =731,769
Volume m =2,411,819
Unique edge count m̿ =842,426
Wedge count s =343,677,541
Claw count z =476,035,640,534
Cross count x =909,343,585,975,693
Square count q =962,735
4-Tour count T4 =1,384,098,060
Maximum degree dmax =57,706
Maximum left degree d1max =57,706
Maximum right degree d2max =1,646
Average degree d =6.393 29
Average left degree d1 =106.177
Average right degree d2 =3.295 87
Fill p =5.068 10 × 10−5
Average edge multiplicity m̃ =2.862 94
Size of LCC N =576,245
Diameter δ =20
50-Percentile effective diameter δ0.5 =6.265 75
90-Percentile effective diameter δ0.9 =8.501 64
Median distance δM =7
Mean distance δm =7.064 48
Gini coefficient G =0.747 683
Balanced inequality ratio P =0.209 926
Left balanced inequality ratio P1 =0.128 030
Right balanced inequality ratio P2 =0.303 091
Relative edge distribution entropy Her =0.848 102
Power law exponent γ =9.072 94
Tail power law exponent γt =3.281 00
Tail power law exponent with p γ3 =3.281 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.461 00
Left p-value p1 =0.000 00
Right tail power law exponent with p γ3,2 =3.321 00
Right p-value p2 =0.061 000 0
Degree assortativity ρ =−0.023 376 8
Degree assortativity p-value pρ =3.765 43 × 10−102
Spectral norm α =1,448.25
Algebraic connectivity a =0.000 109 746
Spectral separation 1[A] / λ2[A]| =1.448 50
Controllability C =709,624
Relative controllability Cr =0.940 542


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

Diameter/density evolution

Inter-event distribution

Node-level inter-event 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] Kevin Emamy and Richard Cameron. CiteULike: A researcher's social bookmarking service. Ariadne, (51), 2007.