Twitch Gamers Social Network
A Twitch (gaming social network) dataset of 168,116 users and 6,797,558 mutual follower edges, collected by Rozemberczki & Sarkar via Twitch public API (2018). Each record contains undirected mutual follower edges, node features (views, mature, life_time, created_at, updated_at, dead_account, language, affiliate). The dataset is notable for its large-scale strongly connected component with no missing attributes, designed for node classification and count data regression. Intended for research into social network analysis, node classification, community detection, and transfer learning in gaming communities.
Cite this dataset at
twitch-gamers.echo.directory
Analytics
The full graph has 168,116 nodes; this view shows the 1,000-node sample the pipeline drew for display. Node size is centrality, colour is community.
Computed over the full corpus.
Record
- Catalog key
twitch-gamers- Authors
- Rozemberczki, Benedek; Sarkar, Rik
- Year
- 2021
- Source paper
- Twitch Gamers: a Dataset for Evaluating Proximity Preserving and Structural Role-based Node Embeddings
- DOI / arXiv
- 10.48550/arXiv.2101.03091
- License
- MIT (repository) (MIT)
- Records
- 168,116
- Nodes
- 168,116
- Edges
- 6,797,558
- Nodes are
- user
- Edges are
- follow
- Attributes
- nodes have attributes; edges have no attributes
- Languages
- en
- Collected
- 2018 (2010s)
- Tasks
- Node classification (binary;
mature, dead_account, affiliate) inferred
From the graph: link prediction, community detection - Region
- Global (inferred: the platform is used worldwide)
Provenance
- Originally published at
- https://github.com/benedekrozemberczki/datasets link checked
- Hosted copy
- Mirrored on echo.directory on 2026-10-09, 89.8 MB across 3 files. Checksums in MANIFEST.json.
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}
}
@misc{https://doi.org/10.48550/arxiv.2101.03091,
doi = {10.48550/ARXIV.2101.03091},
url = {https://arxiv.org/abs/2101.03091},
author = {Rozemberczki, Benedek and Sarkar, Rik},
keywords = {Social and Information Networks (cs.SI), Artificial Intelligence (cs.AI), Machine Learning (cs.LG), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {Twitch Gamers: a Dataset for Evaluating Proximity Preserving and Structural Role-based Node Embeddings},
publisher = {arXiv},
year = {2021},
copyright = {Creative Commons Attribution 4.0 International}
} APA
Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory
Rozemberczki, B., & Sarkar, R. (2021). Twitch Gamers Social Network [Data set]. https://doi.org/10.48550/arXiv.2101.03091
MLA
Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.
Rozemberczki, Benedek, and Rik Sarkar. Twitch Gamers Social Network. 2021, doi.org/10.48550/arXiv.2101.03091.