This is the bipartite picture tagging network of Left nodes represent users and right nodes represents pictures. An edge connects a user with a picture he has tagged.


Internal namepics_ui user–item
Data source
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Interaction network
Node meaningUser, picture
Edge meaningTag assignment
Network formatBipartite, undirected
Edge typeUnweighted, multiple edges


Size n =512,524
Left size n1 =17,122
Right size n2 =495,402
Volume m =2,298,816
Unique edge count m̿ =997,840
Wedge count s =489,164,625
Square count q =19,336,325
4-Tour count T4 =2,113,369,668
Maximum degree dmax =46,571
Maximum left degree d1max =46,571
Maximum right degree d2max =790
Average degree d =8.970 57
Average left degree d1 =134.261
Average right degree d2 =4.640 30
Average edge multiplicity m̃ =2.303 79
Size of LCC N =506,648
Diameter δ =14
50-Percentile effective diameter δ0.5 =5.057 31
90-Percentile effective diameter δ0.9 =5.878 07
Median distance δM =6
Mean distance δm =5.154 40
Gini coefficient G =0.776 842
Balanced inequality ratio P =0.191 994
Left balanced inequality ratio P1 =0.148 075
Right balanced inequality ratio P2 =0.282 309
Relative edge distribution entropy Her =0.838 461
Tail power law exponent γt =2.201 00
Degree assortativity ρ =−0.074 900 8
Degree assortativity p-value pρ =0.000 00
Spectral norm α =1,012.77
Algebraic connectivity a =0.004 221 18
Spectral separation 1[A] / λ2[A]| =2.101 98
Controllability C =478,505
Relative controllability Cr =0.933 625


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

Delaunay graph drawing

Edge weight/multiplicity 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] Nicolas Neubauer and Klaus Obermayer. Analysis of the folksonomy. Unpublished, 2010.