BibSonomy user–item

This is the bipartite user–publication network from BibSonomy. Each edge represents a tag assignment. The network allows multiple edge, i.e., a user may give multiple tags to a single publication. The network is complete as it is taken from the official BibSonomy dump.


Internal namebibsonomy-2ui
NameBibSonomy user–item
Data source
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Interaction network
Dataset timestamp 2010
Node meaningUser, publication
Edge meaningTag assignment
Network formatBipartite, undirected
Edge typeUnweighted, multiple edges
Temporal data Edges are annotated with timestamps


Size n =773,241
Left size n1 =5,794
Right size n2 =767,447
Volume m =2,555,080
Unique edge count m̿ =801,784
Wedge count s =12,835,279,754
Claw count z =394,424,715,096,067
Cross count x =1.037 59 × 1019
Square count q =2,794,766
4-Tour count T4 =51,365,102,888
Maximum degree dmax =428,436
Maximum left degree d1max =428,436
Maximum right degree d2max =341
Average degree d =6.608 75
Average left degree d1 =440.987
Average right degree d2 =3.329 32
Fill p =0.000 180 314
Average edge multiplicity m̃ =3.186 74
Size of LCC N =349,470
Diameter δ =16
50-Percentile effective diameter δ0.5 =3.763 18
90-Percentile effective diameter δ0.9 =5.788 28
Median distance δM =4
Mean distance δm =4.698 34
Gini coefficient G =0.730 014
Balanced inequality ratio P =0.222 665
Left balanced inequality ratio P1 =0.080 483 2
Right balanced inequality ratio P2 =0.324 171
Relative edge distribution entropy Her =0.738 449
Power law exponent γ =29.250 6
Tail power law exponent γt =4.691 00
Tail power law exponent with p γ3 =4.691 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.431 00
Left p-value p1 =0.000 00
Right tail power law exponent with p γ3,2 =5.281 00
Right p-value p2 =0.000 00
Degree assortativity ρ =−0.087 479 1
Degree assortativity p-value pρ =0.000 00
Spectral norm α =1,767.75
Algebraic connectivity a =0.001 069 24
Spectral separation 1[A] / λ2[A]| =1.621 81
Controllability C =761,785
Relative controllability Cr =0.985 184


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

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] Dominik Benz, Andreas Hotho, Robert Jäschke, Beate Krause, Folke Mitzlaff, Christoph Schmitz, and Gerd Stumme. The social bookmark and publication management system BibSonomy. The VLDB J., 19(6):849–875, dec 2010.