arXiv hep-ph

This is the co-citation network of scientific papers from the arXiv's High Energy Physics – Phenomenology (hep-ph) section. An edge between two papers represents a common citing publication. Timestamps denote the date of the citing publication.


Internal nameca-cit-HepPh
NamearXiv hep-ph
Data source
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Co-citation network
Node meaningAuthor
Edge meaningCo-citation
Network formatUnipartite, undirected
Edge typeUnweighted, multiple edges
Temporal data Edges are annotated with timestamps
LoopsDoes not contain loops
Join Is the join of an underlying network


Size n =28,093
Volume m =4,596,803
Unique edge count m̿ =3,148,447
Loop count l =0
Wedge count s =2,097,593,926
Claw count z =862,892,139,927
Cross count x =409,090,345,290,895
Triangle count t =195,758,685
Square count q =69,676,915,730
4-Tour count T4 =565,811,998,438
Maximum degree dmax =11,134
Average degree d =327.256
Fill p =0.007 978 95
Average edge multiplicity m̃ =1.460 02
Size of LCC N =28,045
Diameter δ =9
50-Percentile effective diameter δ0.5 =2.353 74
90-Percentile effective diameter δ0.9 =3.216 57
Median distance δM =3
Mean distance δm =2.827 13
Gini coefficient G =0.670 678
Balanced inequality ratio P =0.239 576
Relative edge distribution entropy Her =0.934 575
Power law exponent γ =1.219 86
Tail power law exponent γt =1.731 00
Degree assortativity ρ =+0.033 384 3
Degree assortativity p-value pρ =0.000 00
Clustering coefficient c =0.279 976
Spectral norm α =1,921.46
Algebraic connectivity a =0.169 297
Spectral separation 1[A] / λ2[A]| =1.120 47
Non-bipartivity bA =0.862 128
Normalized non-bipartivity bN =0.232 408
Algebraic non-bipartivity χ =0.381 300
Spectral bipartite frustration bK =0.000 424 561
Controllability C =11


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

Double Laplacian graph drawing

Delaunay graph drawing

Edge weight/multiplicity distribution

Clustering coefficient distribution

Average neighbor degree distribution

Temporal distribution

Temporal hop distribution

Diameter/density evolution


Inter-event distribution

Node-level inter-event 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] Jure Leskovec, Jon Kleinberg, and Christos Faloutsos. Graph evolution: Densification and shrinking diameters. ACM Trans. Knowl. Discov. from Data, 1(1):1–40, 2007.