Delicious user–item

This network contains user–URL relations from Left nodes represent users, right nodes represent URLs and an edge shows that a user tagged a URL.


Internal namedelicious-ui
NameDelicious user–item
Data source
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Interaction network
Node meaningUser, URL
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 =34,611,302
Left size n1 =833,081
Right size n2 =33,778,221
Volume m =301,186,579
Unique edge count m̿ =101,798,957
Wedge count s =69,264,303,940
Claw count z =108,117,582,742,195
Cross count x =318,897,354,040,560,704
Maximum degree dmax =143,470
Maximum left degree d1max =143,470
Maximum right degree d2max =100,625
Average degree d =17.403 9
Average left degree d1 =361.533
Average right degree d2 =8.916 59
Fill p =3.617 59 × 10−6
Average edge multiplicity m̃ =2.958 64
Size of LCC N =34,323,019
Diameter δ =29
50-Percentile effective diameter δ0.5 =5.093 45
90-Percentile effective diameter δ0.9 =5.833 41
Mean distance δm =5.143 67
Gini coefficient G =0.879 437
Balanced inequality ratio P =0.123 302
Left balanced inequality ratio P1 =0.191 035
Right balanced inequality ratio P2 =0.191 701
Relative edge distribution entropy Her =0.842 841
Power law exponent γ =3.649 70
Tail power law exponent γt =1.761 00
Degree assortativity ρ =−0.031 510 6
Degree assortativity p-value pρ =0.000 00
Spectral norm α =3,694.59


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.