BibSonomy tag–item

This is the bipartite tag–publication network from BibSonomy. The network allows multiple edge, i.e., publications can be tagged multiple times with the same tag. The network is complete as it is taken from the official BibSonomy dump.


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


Size n =972,120
Left size n1 =204,673
Right size n2 =767,447
Volume m =2,555,080
Unique edge count m̿ =2,499,057
Wedge count s =19,526,902,897
Claw count z =1,043,988,925,479,286
Cross count x =4.672 67 × 1019
Square count q =636,346,469
4-Tour count T4 =83,203,483,378
Maximum degree dmax =182,908
Maximum left degree d1max =182,908
Maximum right degree d2max =341
Average degree d =5.256 72
Average left degree d1 =12.483 7
Average right degree d2 =3.329 32
Fill p =1.590 99 × 10−5
Average edge multiplicity m̃ =1.022 42
Size of LCC N =937,063
Diameter δ =22
50-Percentile effective diameter δ0.5 =5.174 78
90-Percentile effective diameter δ0.9 =6.948 13
Median distance δM =6
Mean distance δm =5.540 73
Gini coefficient G =0.666 800
Balanced inequality ratio P =0.251 730
Left balanced inequality ratio P1 =0.134 076
Right balanced inequality ratio P2 =0.324 171
Relative edge distribution entropy Her =0.857 427
Power law exponent γ =2.209 99
Tail power law exponent γt =2.051 00
Tail power law exponent with p γ3 =2.051 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 =3.921 00
Right p-value p2 =0.000 00
Degree assortativity ρ =−0.185 572
Degree assortativity p-value pρ =0.000 00
Spectral norm α =430.870
Algebraic connectivity a =0.000 207 657
Spectral separation 1[A] / λ2[A]| =1.656 96
Controllability C =667,469
Relative controllability Cr =0.686 612


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.