Political books

This is "[a] network of books about US politics published around the time of the 2004 presidential election and sold by the online bookseller Amazon.com. Edges between books represent frequent copurchasing of books by the same buyers."


Internal namedimacs10-polbooks
NamePolitical books
Data sourcehttps://www.cc.gatech.edu/dimacs10/archive/clustering.shtml
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Miscellaneous network
Dataset timestamp 2004
Node meaningBook
Edge meaningCo-purchase
Network formatUnipartite, undirected
Edge typeUnweighted, no multiple edges
LoopsDoes not contain loops
Completeness Is incomplete
Join Is the join of an underlying network
Multiplicity Does not have multiple edges, but the underlying data has
k-Core Only nodes with degree larger than a given threshold are included


Size n =105
Volume m =441
Loop count l =0
Wedge count s =4,822
Claw count z =22,689
Cross count x =91,898
Triangle count t =560
Square count q =3,509
4-Tour count T4 =48,242
Maximum degree dmax =25
Average degree d =8.400 00
Fill p =0.080 769 2
Size of LCC N =105
Diameter δ =7
50-Percentile effective diameter δ0.5 =2.209 39
90-Percentile effective diameter δ0.9 =4.050 49
Median distance δM =3
Mean distance δm =2.841 11
Gini coefficient G =0.327 978
Balanced inequality ratio P =0.375 283
Relative edge distribution entropy Her =0.961 592
Power law exponent γ =1.790 96
Tail power law exponent γt =2.621 00
Degree assortativity ρ =−0.127 896
Degree assortativity p-value pρ =0.000 139 766
Clustering coefficient c =0.348 403
Spectral norm α =11.932 6
Algebraic connectivity a =0.323 607
Non-bipartivity bA =0.564 121
Normalized non-bipartivity bN =0.448 155
Algebraic non-bipartivity χ =1.276 20
Spectral bipartite frustration bK =0.037 982 1
Controllability C =2
Relative controllability Cr =0.019 047 6


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

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 ]