DNC co-recipients

This is the undirected network of people having received the same email in the 2016 Democratic National Committee email leak. The Democratic National Committee (DNC) is the formal governing body for the United States Democratic Party. A dump of emails of the DNC was leaked in 2016, and this dataset contains persons from that dump as nodes, and an edge when two persons received the same email, i.e., when two persons were on the recipient list of the same email. Multiple edges indicate multiple emails.


Internal namednc-corecipient
NameDNC co-recipients
Data sourcehttp://www.rene-pickhardt.de/extracting-2-social-network-graphs-from-the-democratic-national-committee-email-corpus-on-wikileaks/
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Online contact network
Dataset timestamp 2016
Node meaningPerson
Edge meaningCo-recipientship
Network formatUnipartite, undirected
Edge typeUnweighted, multiple edges
LoopsDoes not contain loops
Snapshot Is a snapshot and likely to not contain all data
Join Is the join of an underlying network


Size n =2,029
Volume m =136,602
Unique edge count m̿ =12,085
Loop count l =0
Wedge count s =955,910
Claw count z =86,121,142
Cross count x =5,511,669,921
Triangle count t =174,677
Square count q =10,408,369
4-Tour count T4 =87,111,450
Maximum degree dmax =462
Average degree d =134.650
Fill p =0.029 478 1
Average edge multiplicity m̃ =11.303 4
Size of LCC N =849
Diameter δ =8
50-Percentile effective diameter δ0.5 =2.204 17
90-Percentile effective diameter δ0.9 =3.306 08
Median distance δM =3
Mean distance δm =2.713 72
Gini coefficient G =0.889 309
Balanced inequality ratio P =0.109 475
Relative edge distribution entropy Her =0.842 080
Power law exponent γ =1.583 17
Tail power law exponent γt =1.451 00
Tail power law exponent with p γ3 =1.451 00
p-value p =0.000 00
Degree assortativity ρ =−0.124 892
Degree assortativity p-value pρ =2.796 50 × 10−73
Clustering coefficient c =0.548 201
Spectral norm α =3,522.12
Algebraic connectivity a =0.211 770
Spectral separation 1[A] / λ2[A]| =3.867 82
Non-bipartivity bA =0.755 203
Normalized non-bipartivity bN =0.274 849
Algebraic non-bipartivity χ =0.368 608
Spectral bipartite frustration bK =0.003 767 20
Controllability C =283
Relative controllability Cr =0.312 362


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


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 ]