DBLP
This is the citation network of DBLP, a database of scientific publications
such as papers and books. Each node in the network is a publication, and each
edge represents a citation of a publication by another publication. In other
words, the directed edge (A → B) denotes that publication A cites publication
B. Publications are allowed to cite themselves, and therefore the network
contains loops. The original dataset contains a small number (<100) of
erroneous duplicate edges, i.e., a paper citing another paper multiple times.
These have been removed from this version of the dataset.
Metadata
Statistics
Size  n =  12,590

Volume  m =  49,759

Loop count  l =  15

Wedge count  s =  2,124,720

Claw count  z =  172,872,369

Cross count  x =  22,368,563,858

Triangle count  t =  43,896

Square count  q =  787,154

4Tour count  T_{4} =  14,895,384

Maximum degree  d_{max} =  714

Maximum outdegree  d^{+}_{max} =  617

Maximum indegree  d^{−}_{max} =  227

Average degree  d =  7.904 53

Fill  p =  0.000 313 921

Size of LCC  N =  12,494

Size of LSCC  N_{s} =  240

Relative size of LSCC  N^{r}_{s} =  0.019 062 7

Diameter  δ =  10

50Percentile effective diameter  δ_{0.5} =  3.847 50

90Percentile effective diameter  δ_{0.9} =  4.997 88

Median distance  δ_{M} =  4

Mean distance  δ_{m} =  4.372 20

Gini coefficient  G =  0.657 631

Balanced inequality ratio  P =  0.234 611

Outdegree balanced inequality ratio  P_{+} =  0.361 683

Indegree balanced inequality ratio  P_{−} =  0.262 244

Relative edge distribution entropy  H_{er} =  0.907 783

Power law exponent  γ =  1.837 27

Tail power law exponent  γ_{t} =  3.391 00

Tail power law exponent with p  γ_{3} =  3.391 00

pvalue  p =  0.466 000

Outdegree tail power law exponent with p  γ_{3,o} =  3.611 00

Outdegree pvalue  p_{o} =  0.000 00

Indegree tail power law exponent with p  γ_{3,i} =  2.711 00

Indegree pvalue  p_{i} =  0.054 000 0

Degree assortativity  ρ =  −0.045 724 6

Degree assortativity pvalue  p_{ρ} =  4.224 43 × 10^{−47}

In/outdegree correlation  ρ^{±} =  +0.011 711 9

Clustering coefficient  c =  0.061 979 0

Directed clustering coefficient  c^{±} =  0.096 706 4

Spectral norm  α =  43.054 6

Operator 2norm  ν =  34.102 3

Cyclic eigenvalue  π =  4.676 83

Algebraic connectivity  a =  0.085 199 2

Spectral separation  λ_{1}[A] / λ_{2}[A] =  1.390 85

Reciprocity  y =  0.004 642 38

Nonbipartivity  b_{A} =  0.331 103

Normalized nonbipartivity  b_{N} =  0.047 487 4

Algebraic nonbipartivity  χ =  0.085 170 6

Spectral bipartite frustration  b_{K} =  0.002 682 08

Controllability  C =  9,453

Relative controllability  C_{r} =  0.750 834

Plots
Matrix decompositions plots
Downloads
References
[1]

Jérôme Kunegis.
KONECT – The Koblenz Network Collection.
In Proc. Int. Conf. on World Wide Web Companion, pages
1343–1350, 2013.
[ http ]

[2]

Michael Ley.
The DBLP computer science bibliography: Evolution, research issues,
perspectives.
In Proc. Int. Symposium on String Process. and Inf. Retr.,
pages 1–10, 2002.
