YouTube Social Network v1

A multi-dimensional YouTube network crawled in December 2008 at Arizona State University (Tang & Liu), from the ASU Social Computing Data Repository: 15,088 active users and five weighted, undirected interaction layers with 13,628,895 edges in all. The layers are contacts (76,765), shared friends (1,940,806), shared subscriptions (5,574,249), shared subscribers (2,239,440) and shared favourite videos (3,797,635); each pair is listed once. Suitable for multi-layer network analysis and community detection.

#Arizona state university#Multi relational network#Syracuse data lab#Weighted network#Zafarani

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Analytics

The interactive network needs JavaScript.

· graph.json

The full graph has 15,088 nodes; this view shows the 1,000-node sample the pipeline drew for display. Node size is centrality, colour is community.

15.1K
Nodes
13.6M
Edges
9.55e-02
Density
3
Components
-0.02353
Assortativity
0.0%
Reciprocity
102
Bridges
Most central nodes
11890.5447
240.5344
1720.5152
55920.5093
70050.509
1410.507
26940.5066
69670.5022
132150.498
119780.4934
Content metrics

13,628,895 records scored · min–maxmean ± 0.675 σ (the interquartile range if the values are roughly normal)mean

interaction intensityμ 2.42 ± 2.813
min 1max 326
interaction typeavg 3.57 / 5
1std 1.065

Computed over the full corpus.

Record

Catalog key
youtube-v1
Authors
Tang, Lei; Wang, Xufei; Liu, Huan; Zafarani, Reza
Year
2009
Source paper
Uncovering Groups via Heterogeneous Interaction Analysis
DOI / arXiv
10.1109/icdm.2009.20
License
Academic Use (see Syracuse Data Lab terms) (LicenseRef-Research-Only)
Records
15,088
Nodes
15,088
Edges
13,628,895
Nodes are
user
Edges are
interaction
Attributes
nodes have no attributes; edges have attributes
Languages
en
Collected
2007-2008 (2000s)
Tasks
From the graph: link prediction, community detection
Region
Global (inferred: the platform is used worldwide)

Provenance

Originally published at
https://datasets.syr.edu link checked
Hosted copy
Mirrored on echo.directory on 2026-10-09, 162.8 MB across 7 files. Checksums in MANIFEST.json.

Citations

Uncoverning Groups via Heterogeneous Interaction Analysis
Lei Tang, Xufei Wang, Huan Liu
Journal Article · 2009 Ninth IEEE International Conference on Data Mining · 2009

190
citations
well cited
26
influential citations
14% of all citations

Cited by

Show all 10

Citation data from Semantic Scholar, retrieved 2026-10-22.

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{Tang_2009,
  title     = {Uncovering Groups via Heterogeneous Interaction Analysis},
  doi       = {10.1109/icdm.2009.20},
  booktitle = {2009 Ninth IEEE International Conference on Data Mining},
  publisher = {IEEE},
  author    = {Tang, Lei and Wang, Xufei and Liu, Huan},
  year      = {2009},
  month     = Dec,
  pages     = {503--512}
}

@misc{Zafarani_2009_asu,
  title        = {Social Computing Data Repository at {ASU}},
  author       = {Zafarani, Reza and Liu, Huan},
  year         = {2009},
  howpublished = {\url{http://socialcomputing.asu.edu}},
  note         = {Tempe, AZ: Arizona State University, School of Computing, Informatics and Decision Systems Engineering}
}

APA

Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory

Tang, L., Wang, X., Liu, H., & Zafarani, R. (2009). YouTube Social Network v1 [Data set]. https://doi.org/10.1109/icdm.2009.20

MLA

Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.

Tang, Lei, et al. YouTube Social Network v1. 2009, doi.org/10.1109/icdm.2009.20.

BibTeX · RIS · CSL-JSON

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