Youtube links

This is the social network of Youtube users and their connections. The network is directed. The dataset was crawled from the YouTube website and may be incomplete.


Internal nameyoutube-links
NameYoutube links
Data source
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Online social network
Node meaningUser
Edge meaningLink
Network formatUnipartite, directed
Edge typeUnweighted, no multiple edges
ReciprocalContains reciprocal edges
Directed cyclesContains directed cycles
LoopsDoes not contain loops
Snapshot Is a snapshot and likely to not contain all data


Size n =1,138,499
Volume m =4,942,297
Loop count l =0
Wedge count s =1,472,987,114
Claw count z =33,377,841,563,982
Cross count x =379,296,866,521,715,648
Triangle count t =3,049,419
Square count q =467,434,016
4-Tour count T4 =9,637,401,158
Maximum degree dmax =54,051
Maximum outdegree d+max =28,564
Maximum indegree dmax =25,487
Average degree d =8.682 13
Fill p =3.813 01 × 10−6
Size of LCC N =1,134,885
Size of LSCC Ns =509,245
Relative size of LSCC Nrs =0.447 295
Diameter δ =24
50-Percentile effective diameter δ0.5 =4.758 88
90-Percentile effective diameter δ0.9 =6.775 73
Median distance δM =5
Mean distance δm =5.434 46
Gini coefficient G =0.775 350
Balanced inequality ratio P =0.189 072
Outdegree balanced inequality ratio P+ =0.212 471
Indegree balanced inequality ratio P =0.222 466
Relative edge distribution entropy Her =0.862 468
Power law exponent γ =2.431 92
Tail power law exponent γt =2.141 00
Degree assortativity ρ =−0.036 881 9
Degree assortativity p-value pρ =0.000 00
In/outdegree correlation ρ± =+0.921 861
Clustering coefficient c =0.006 210 68
Directed clustering coefficient c± =0.007 503 64
Spectral norm α =392.305
Operator 2-norm ν =199.826
Cyclic eigenvalue π =193.324
Algebraic connectivity a =0.004 229 03
Reciprocity y =0.789 920
Non-bipartivity bA =0.153 139
Normalized non-bipartivity bN =0.002 045 96
Spectral bipartite frustration bK =0.000 202 591


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

Hop distribution

In/outdegree scatter plot

Clustering coefficient 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] Alan Mislove, Massimiliano Marcon, Krishna P. Gummadi, Peter Druschel, and Bobby Bhattacharjee. Measurement and analysis of online social networks. In Proc. Internet Measurement Conf., 2007.