EU Research Institution Email Network
A European research institution internal email system dataset of 986 employees and 332,334 directed email interactions across 42 departments, collected by Leskovec et al. via SNAP (anonymized institutional email logs). Each record contains sender employee ID, recipient employee ID, Unix timestamp, and department label per employee (42 departments). Temporal directed email communication network from a European research institution with ground-truth department labels for all 986 employees — enabling evaluation of community detection algorithms against known organizational structure.. Suitable for community detection benchmarking, organizational network analysis, temporal email network analysis, higher-order graph clustering.
Cite this dataset at
email-eu-core.echo.directory
Analytics
Node size is centrality, colour is community. Hover a node for details; click one to isolate its community.
Computed over the full corpus.
Record
- Catalog key
email-eu-core- Authors
- Yin, Hao; Benson, Austin R.; Leskovec, Jure; Gleich, David F.
- Year
- 2017
- Source paper
- Local Higher-order Graph Clustering
- DOI / arXiv
- 10.1145/3097983.3098069
- License
- Academic use (SNAP — Stanford Network Analysis Project) (LicenseRef-Research-Only)
- Records
- 986
- Nodes
- 986
- Edges
- 24,929 (directed)
- Nodes are
- employee
- Edges are
- Attributes
- nodes have attributes; edges have no attributes
- Languages
- en
- Collected
- 2003–2005 (2000s)
- Tasks
- From the graph: link prediction, community detection
Provenance
- Originally published at
- https://snap.stanford.edu/data/email-Eu-core-temporal.html link checked
- Hosted copy
- Mirrored on echo.directory on 2026-10-02, 1.6 MB across 2 files. Checksums in MANIFEST.json.
Citations
Local Higher-Order Graph Clustering
Hao Yin, Austin R. Benson, J. Leskovec, D. Gleich
Journal Article · Knowledge Discovery and Data Mining · 2017
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Citation data from Semantic Scholar, retrieved 2026-10-19.
How to cite
BibTeX
@misc{echo2026,
title = {ECHO: Exploratory Compendium of Humanity Online},
author = {Switzer, Braden and Zafarani, Reza},
year = {2026},
url = {https://echo.directory},
note = {Syracuse University}
}
@inproceedings{yin2017local,
title = {Local Higher-order Graph Clustering},
author = {Yin, Hao and Benson, Austin R. and Leskovec, Jure and Gleich, David F.},
booktitle = {Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
pages = {555--564},
year = {2017},
doi = {10.1145/3097983.3098069}
} APA
Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory
Yin, H., Benson, A. R., Leskovec, J., & Gleich, D. F. (2017). EU Research Institution Email Network [Data set]. https://doi.org/10.1145/3097983.3098069
MLA
Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.
Yin, Hao, et al. EU Research Institution Email Network. 2017, doi.org/10.1145/3097983.3098069.