YouTube (v2) Friendship Network

AnalyzedLargegraphYouTubeSocial graph

A YouTube (friendship network) dataset of 1,138,499 users and 2,990,443 friendship edges, collected by Tang & Liu via YouTube crawl (2009). Each record contains user-user friendship edges, group memberships (47 groups), and user IDs. The dataset is notable for its classic social network dataset with explicit group memberships, used as a benchmark for latent social dimensions and collective behavior learning. Intended for research into social network analysis, community detection, group membership prediction, and relational learning in social media.

#Friendship#Group membership#Latent social dimension

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· graph.json

The full graph has 1,138,499 nodes; this view shows the 1,000-node sample the pipeline drew for display. Node size is centrality, colour is community.

1.1M
Nodes
3M
Edges
4.61e-06
Density
930
Components
-0.03687
Assortativity
0.0%
Reciprocity
669.6K
Bridges
Most central nodes
10720.02526
3630.01286
356610.00991
1060.00919
4827090.00857
6446030.00777
9290.00695
8080.00536
278370.00474
1086240.0043

Computed over the full corpus.

Record

Catalog key
youtube-v2
Authors
Tang, Lei; Liu, Huan
Year
2009
Source paper
Relational Learning via Latent Social Dimensions
DOI / arXiv
10.1145/1557019.1557109
License
Academic Use (see Syracuse Data Lab terms) (LicenseRef-Research-Only)
Records
1,138,499
Nodes
1,138,499
Edges
2,990,443
Nodes are
user
Edges are
friendship
Attributes
nodes have attributes; edges have no attributes
Languages
en
Collected
2009 (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, 45.0 MB across 5 files. Checksums in MANIFEST.json.

Citations

Relational learning via latent social dimensions
Lei Tang, Huan Liu
Journal Article · Knowledge Discovery and Data Mining · 2009

852
citations
well cited
80
influential citations
9% of all citations

Cited by

Show all 10

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{tang2009relational,
  title     = {{Relational Learning via Latent Social Dimensions}},
  author    = {Tang, Lei and Liu, Huan},
  booktitle = {Proceedings of the 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'09)},
  pages     = {817--826},
  year      = {2009},
  doi       = {10.1145/1557019.1557109}
}

APA

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

Tang, L., & Liu, H. (2009). YouTube (v2) Friendship Network [Data set]. https://doi.org/10.1145/1557019.1557109

MLA

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

Tang, Lei, and Huan Liu. YouTube (v2) Friendship Network. 2009, doi.org/10.1145/1557019.1557109.

BibTeX · RIS · CSL-JSON

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