This is the trust network from the online social network Epinions. Nodes are users of Epinions and directed edges represent trust between the users.


Internal namesoc-Epinions1
Data sourcehttp://snap.stanford.edu/data/soc-Epinions1.html
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Online social network
Node meaningUser
Edge meaningTrust
Network formatUnipartite, directed
Edge typeUnweighted, no multiple edges
ReciprocalContains reciprocal edges
Directed cyclesContains directed cycles
LoopsDoes not contain loops


Size n =75,879
Volume m =508,837
Wedge count s =74,201,120
Claw count z =27,111,469,575
Cross count x =9,737,182,087,729
Triangle count t =1,624,481
Square count q =166,635,817
4-Tour count T4 =1,630,702,496
Maximum degree dmax =3,079
Maximum outdegree d+max =1,801
Maximum indegree dmax =3,035
Average degree d =13.411 8
Fill p =8.837 74 × 10−5
Size of LCC N =75,877
Size of LSCC Ns =32,223
Relative size of LSCC Nrs =0.424 663
Diameter δ =15
50-Percentile effective diameter δ0.5 =3.816 09
90-Percentile effective diameter δ0.9 =5.258 77
Median distance δM =4
Mean distance δm =4.400 33
Gini coefficient G =0.814 342
Relative edge distribution entropy Her =0.845 432
Power law exponent γ =2.025 80
Tail power law exponent γt =1.691 00
Degree assortativity ρ =−0.040 645 7
Degree assortativity p-value pρ =0.000 00
In/outdegree correlation ρ± =+0.736 595
Clustering coefficient c =0.065 678 8
Spectral norm α =245.999
Operator 2-norm ν =139.616
Cyclic eigenvalue π =106.528
Algebraic connectivity a =0.022 466 4
Reciprocity y =0.405 226
Non-bipartivity bA =0.723 602
Normalized non-bipartivity bN =0.016 785 3
Spectral bipartite frustration bK =0.000 753 884


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

In/outdegree scatter plot

Clustering coefficient distribution

Average neighbor degree 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] Matthew Richardson, Rakesh Agrawal, and Pedro Domingos. Trust management for the semantic web. In Proc. Int. Semant. Web Conf., pages 351–368. 2003.