Delicious user–tag

This network contains user–tag relations from Left nodes represent users, right nodes represent tags and an edge shows that a user tagged an URL using the tag represented by the right node.


Internal namedelicious-ut
NameDelicious user–tag
Data source
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Interaction network
Node meaningUser, tag
Edge meaningTag assignment
Network formatBipartite, undirected
Edge typeUnweighted, multiple edges
Temporal data Edges are annotated with timestamps
Snapshot Is a snapshot and likely to not contain all data


Size n =5,345,180
Left size n1 =833,081
Right size n2 =4,512,099
Volume m =301,186,579
Unique edge count m̿ =81,989,133
Wedge count s =1,445,587,961,389
Claw count z =58,243,254,727,040,968
Cross count x =2.489 28 × 1021
Maximum degree dmax =4,358,622
Maximum left degree d1max =143,470
Maximum right degree d2max =4,358,622
Average degree d =112.695
Average left degree d1 =361.533
Average right degree d2 =66.750 9
Fill p =2.181 17 × 10−5
Average edge multiplicity m̃ =3.673 49
Size of LCC N =5,339,821
Diameter δ =14
50-Percentile effective diameter δ0.5 =3.453 45
90-Percentile effective diameter δ0.9 =4.588 55
Mean distance δm =3.996 38
Gini coefficient G =0.958 877
Balanced inequality ratio P =0.064 980 4
Left balanced inequality ratio P1 =0.191 035
Right balanced inequality ratio P2 =0.045 447 5
Relative edge distribution entropy Her =0.777 832
Power law exponent γ =2.101 20
Tail power law exponent γt =1.471 00
Degree assortativity ρ =−0.129 906
Degree assortativity p-value pρ =0.000 00
Spectral norm α =55,753.5


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 normalized adjacency matrix

Degree assortativity

Hop distribution

Edge weight/multiplicity distribution

Temporal distribution

Diameter/density evolution



[1] Jérôme Kunegis. KONECT – The Koblenz Network Collection. In Proc. Int. Conf. on World Wide Web Companion, pages 1343–1350, 2013. [ http ]
[2] Robert Wetzker, Carsten Zimmermann, and Christian Bauckhage. Analyzing social bookmarking systems: A cookbook. In Proc. Mining Soc. Data Workshop, pages 26–30, 2008.