Slashdot Zoo

This is the signed social network of users of the technology news site Slashdot (, connected by directed "friend" and "foe" relations. The "friend" and "foe" labels are used on Slashdot to mark users, and influence the scores as seen by each user. For instance, If user A marks user B as a foe, the score of user B's posts will be decreased as shown to user A.


Internal nameslashdot-zoo
NameSlashdot Zoo
Data source
Consistency checkDataset passed all tests
Online social network
Dataset timestamp 1997 ⋯ 2009
Node meaningUser
Edge meaningFriend/foe
Network formatUnipartite, directed
Edge typeSigned, no multiple edges
ReciprocalContains reciprocal edges
Directed cyclesContains directed cycles
LoopsDoes not contain loops


Size n =79,120
Volume m =515,397
Average degree d =13.028 2
Maximum degree dmax =2,543
Maximum outdegree d+max =426
Maximum indegree dmax =2,529
Fill p =8.234 15 × 10−5
Negativity ζ =0.239 074
Wedge count s =67,962,178
Claw count z =18,027,108,870
Cross count x =6,450,174,110,946
Size of LCC N =79,116
Relative size of LCC Nrel =0.999 949
Size of LSCC Ns =26,997
Relative size of LSCC Nrels =0.341 216
Degree assortativity ρ =−0.074 604 4
Degree assortativity p-value pρ =0.000 00
In/outdegree correlation ρ± =+0.386 575
Spectral norm ‖A‖2 =52.183 3
Gini coefficient G =0.774 219
Power law exponent γ =1.819 03
Tail power law exponent γt =2.181 00
Relative edge distribution entropy Her =0.870 898
Clustering coefficient c =0.023 748 4
Triangle count t =537,997
Diameter δ =12
50-Percentile effective diameter δ0.5 =3.483 48
90-Percentile effective diameter δ0.9 =4.584 41
Mean distance δm =3.990 80
Reciprocity y =0.184 968
4-Tour count T4 =660,096,934
Square count q =48,414,095
Algebraic connectivity a =0.008 863 49


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

Item rating evolution

Edge weight/multiplicity distribution

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] Jérôme Kunegis, Andreas Lommatzsch, and Christian Bauckhage. The Slashdot Zoo: Mining a social network with negative edges. In Proc. Int. World Wide Web Conf., pages 741–750, 2009. [ http ]