Matrix: SNAP/email-EuAll
Description: Email network from a EU research institution
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| (bipartite graph drawing) | (graph drawing of A+A') |
 |
 |
| Matrix properties | |
| number of rows | 265,214 |
| number of columns | 265,214 |
| nonzeros | 420,045 |
| # strongly connected comp. | 231,000 |
| explicit zero entries | 0 |
| nonzero pattern symmetry | 26% |
| numeric value symmetry | 26% |
| type | binary |
| structure | unsymmetric |
| Cholesky candidate? | no |
| positive definite? | no |
| author | J. Leskovec, J. Kleinberg and C. Faloutsos |
| editor | J. Leskovec |
| date | 2005 |
| kind | directed graph |
| 2D/3D problem? | no |
Notes:
Networks from SNAP (Stanford Network Analysis Platform) Network Data Sets,
Jure Leskovec http://snap.stanford.edu/data/index.html
email jure at cs.stanford.edu
EU email communication network
Dataset information
The network was generated using email data from a large European research
institution. For a period from October 2003 to May 2005 (18 months) we have
anonymized information about all incoming and outgoing email of the research
institution. For each sent or received email message we know the time, the
sender and the recipient of the email. Overall we have 3,038,531 emails between
287,755 different email addresses. Note that we have a complete email graph for
only 1,258 email addresses that come from the research institution.
Furthermore, there are 34,203 email addresses that both sent and received email
within the span of our dataset. All other email addresses are either
non-existing, mistyped or spam.
Given a set of email messages, each node corresponds to an email address. We
create a directed edge between nodes i and j, if i sent at least one message to
j.
Dataset statistics
Nodes 265214
Edges 420045
Nodes in largest WCC 224832 (0.848)
Edges in largest WCC 395270 (0.941)
Nodes in largest SCC 34203 (0.129)
Edges in largest SCC 151930 (0.362)
Average clustering coefficient 0.3093
Number of triangles 267313
Fraction of closed triangles 0.004106
Diameter (longest shortest path) 13
90-percentile effective diameter 4.5
Source (citation)
J. Leskovec, J. Kleinberg and C. Faloutsos. Graph Evolution: Densification and
Shrinking Diameters. ACM Transactions on Knowledge Discovery from Data (ACM
TKDD), 1(1), 2007.
Files
File Description
email-EuAll.txt.gz Email network of a large European Research Institution
For a description of the statistics displayed above, click here.
Maintained by Tim Davis, last updated 12-Mar-2014.
Matrix pictures by cspy, a MATLAB function in the CSparse package.
Matrix graphs by Yifan Hu, AT&T Labs Visualization Group.