Marvel

This is the fictional collaboration network of characters in works of Marvel, a publisher of comic books based in the United States of America. The network is bipartite. Nodes are characters and works, and an edge is present when a character appears in a work. The dataset takes works only into account if thy were published starting in 1961. To cite the paper: "We only consider here comics published after Issue 1 of Fantastic Four (dated November 1961), which is understood as the point of departure of the Marvel Age of Comics." The data was extracted from the Marvel Chronology Project (MCP) created by Russ Chappell (www.chronologyproject.com). The dataset does contain the names of the characters, even though a few a empty strings.

Metadata

CodeMA
Internal namemarvel
NameMarvel
Data sourcehttp://bioinfo.uib.es/~joemiro/marvel.html
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Category
Miscellaneous network
Dataset timestamp 1961 ⋯ 2002
Node meaningCharacter, work
Edge meaningAppearance
Network formatBipartite, undirected
Edge typeUnweighted, no multiple edges

Statistics

Size n =25,914
Left size n1 =6,486
Right size n2 =19,428
Volume m =96,662
Wedge count s =12,869,214
Claw count z =3,054,666,860
Cross count x =795,147,934,751
Triangle count t =0
Square count q =10,709,594
4-Tour count T4 =137,346,932
Maximum degree dmax =1,625
Maximum left degree d1max =1,625
Maximum right degree d2max =111
Average degree d =7.460 21
Average left degree d1 =14.903 2
Average right degree d2 =4.975 40
Fill p =0.000 767 098
Size of LCC N =19,365
Diameter δ =11
50-Percentile effective diameter δ0.5 =3.955 58
90-Percentile effective diameter δ0.9 =5.442 45
Median distance δM =4
Mean distance δm =4.491 85
Gini coefficient G =0.615 843
Balanced inequality ratio P =0.276 929
Left balanced inequality ratio P1 =0.181 385
Right balanced inequality ratio P2 =0.347 541
Relative edge distribution entropy Her =0.895 614
Power law exponent γ =1.635 85
Tail power law exponent γt =2.181 00
Tail power law exponent with p γ3 =2.181 00
p-value p =0.048 000 0
Left tail power law exponent with p γ3,1 =1.951 00
Left p-value p1 =0.003 000 00
Right tail power law exponent with p γ3,2 =4.681 00
Right p-value p2 =0.033 000 0
Degree assortativity ρ =−0.017 701 3
Degree assortativity p-value pρ =3.717 11 × 10−8
Clustering coefficient c =0.000 00
Spectral norm α =69.136 5
Algebraic connectivity a =0.042 315 6
Spectral separation 1[A] / λ2[A]| =1.290 64
Controllability C =9,364
Relative controllability Cr =0.481 985

Plots

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

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] Ricardo Alberich, J. Miro-Julia, and Francesc Rosselló. Marvel universe looks almost like a real social network. 2002. [ http ]