The Enron email network consists of 1,148,072 emails sent between employees of Enron between 1999 and 2003. Nodes in the network are individual employees and edges are individual emails. It is possible to send an email to oneself, and thus this network contains loops.


Internal nameenron
Data sourcehttp://www.cs.cmu.edu/~enron/
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Communication network
Dataset timestamp 1999 ⋯ 2003
Node meaningEmployee
Edge meaningEmail
Network formatUnipartite, directed
Edge typeUnweighted, multiple edges
Temporal data Edges are annotated with timestamps
ReciprocalContains reciprocal edges
Directed cyclesContains directed cycles
LoopsContains loops


Size n =87,273
Volume m =1,148,072
Unique edge count m̿ =321,918
Wedge count s =49,424,399
Claw count z =13,894,959,120
Cross count x =3,805,295,597,320
Triangle count t =1,180,387
Square count q =92,985,807
4-Tour count T4 =942,178,964
Maximum degree dmax =38,785
Maximum outdegree d+max =32,619
Maximum indegree dmax =6,166
Average degree d =26.309 9
Fill p =4.226 54 × 10−5
Average edge multiplicity m̃ =3.566 35
Size of LCC N =84,384
Size of LSCC Ns =9,164
Relative size of LSCC Nrs =0.105 004
Diameter δ =14
50-Percentile effective diameter δ0.5 =4.405 46
90-Percentile effective diameter δ0.9 =5.790 34
Median distance δM =5
Mean distance δm =4.903 26
Balanced inequality ratio P =0.100 618
Outdegree balanced inequality ratio P+ =0.106 510
Indegree balanced inequality ratio P =0.134 857
Power law exponent γ =2.651 60
Tail power law exponent γt =1.761 00
Tail power law exponent with p γ3 =1.761 00
p-value p =0.000 00
Outdegree tail power law exponent with p γ3,o =2.301 00
Outdegree p-value po =0.000 00
Indegree tail power law exponent with p γ3,i =2.871 00
Indegree p-value pi =0.351 000
Degree assortativity ρ =−0.167 768
Degree assortativity p-value pρ =0.000 00
In/outdegree correlation ρ± =+0.403 110
Clustering coefficient c =0.071 648 0
Spectral norm α =7,808.15
Operator 2-norm ν =3,904.14
Cyclic eigenvalue π =3,904.00
Algebraic connectivity a =0.004 157 70
Reciprocity y =0.146 497
Non-bipartivity bA =0.622 292
Spectral bipartite frustration bK =8.928 20 × 10−5
Controllability C =77,596
Relative controllability Cr =0.889 118


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

In/outdegree scatter plot

Edge weight/multiplicity distribution

Clustering coefficient 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] Bryan Klimt and Yiming Yang. The Enron corpus: A new dataset for email classification research. In Proc. Eur. Conf. on Mach. Learn., pages 217–226, 2004.