This is the co-authorship network from the "astrophysics" section (astro-ph) of arXiv. Nodes are authors and an edge denotes a collaboration.


Internal namedimacs10-astro-ph
Data source
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Co-authorship network
Dataset timestamp 1995-01-01 ⋯ 1999-12-31
Node meaningAuthor
Edge meaningCo-authorship
Network formatUnipartite, undirected
Edge typeUnweighted, no multiple edges
LoopsDoes not contain loops
Join Is the join of an underlying network
Multiplicity Does not have multiple edges, but the underlying data has


Size n =16,046
Volume m =121,251
Loop count l =0
Wedge count s =5,325,457
Claw count z =163,827,498
Cross count x =6,615,074,549
Triangle count t =756,019
Square count q =21,648,652
4-Tour count T4 =194,733,546
Maximum degree dmax =360
Average degree d =15.112 9
Fill p =0.000 941 909
Size of LCC N =14,845
Diameter δ =14
50-Percentile effective diameter δ0.5 =4.321 41
90-Percentile effective diameter δ0.9 =7.011 94
Median distance δM =5
Mean distance δm =5.108 49
Gini coefficient G =0.591 788
Balanced inequality ratio P =0.273 350
Relative edge distribution entropy Her =0.934 837
Power law exponent γ =1.494 83
Tail power law exponent γt =3.751 00
Tail power law exponent with p γ3 =3.751 00
p-value p =0.101 000
Degree assortativity ρ =+0.235 462
Degree assortativity p-value pρ =0.000 00
Clustering coefficient c =0.425 890
Spectral norm α =73.886 8
Algebraic connectivity a =0.030 183 6
Non-bipartivity bA =0.663 931
Normalized non-bipartivity bN =0.088 359 2
Spectral bipartite frustration bK =0.002 242 24


Fruchterman–Reingold graph drawing

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

Delaunay graph drawing

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] Mark E. J. Newman. The structure of scientific collaboration networks. Proc. Natl. Acad. Sci. U.S.A., 98(2):404–409, 2001.