GEMSEC Facebook Page-Page Networks (Cumulative)
A Facebook (social media platform) dataset of 134,833 Facebook pages and 1,379,403 undirected mutual-like edges across 8 page categories (company, politician, tvshow, government, artist, new_sites, public_figure, athletes), collected by Rozemberczki et al. via Facebook Graph API, distributed via GEMSEC/SNAP. Each record contains undirected edges between Facebook pages representing mutual likes; pages categorized as company, politician, TV show, government, artist, news site, public figure, or athlete; node IDs namespaced by category. The dataset is notable for its multi-category Facebook page network with known ground-truth category labels per node, enabling direct evaluation of community detection and node classification algorithms across heterogeneous page types. Intended for research into community detection, node classification, graph embedding, cross-category network comparison, and social media page recommendation research.
Cite this dataset at
gemsec-facebook.echo.directory
Analytics
The full graph has 134,833 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
gemsec-facebook- Authors
- Rozemberczki, Benedek; Davies, Ryan; Sarkar, Rik; Sutton, Charles
- Year
- 2019
- Source paper
- GEMSEC: Graph Embedding with Self Clustering
- DOI / arXiv
- 10.1145/3341161.3342890
- License
- GNU GPL 3.0 (GPL-3.0-only)
- Records
- 134,833
- Nodes
- 134,833
- Edges
- 1,379,403
- Nodes are
- facebook page
- Edges are
- mutual like
- Attributes
- nodes have no attributes; edges have no attributes
- Languages
- en
- Collected
- 2017-11 (2010s)
- Tasks
- From the graph: link prediction, community detection
- Region
- Global (inferred: the platform is used worldwide)
Provenance
- Originally published at
- https://snap.stanford.edu/data/gemsec-Facebook.html link checked
- Hosted copy
- Mirrored on echo.directory on 2026-10-09, 14.7 MB across 10 files. Checksums in MANIFEST.json.
Citations
GEMSEC: Graph Embedding with Self Clustering
Benedek Rozemberczki, Ryan Davies, Rik Sarkar, Charles Sutton
Book · International Conference on Advances in Social Networks Analysis and Mining · 2018
Cited by
- Multi-scale Attributed Node Embedding
Benedek Rozemberczki, Carl Allen et al. · J. Complex Networks · 2019 · cited 1.2K× - Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models
Benedek Rozemberczki, Rik Sarkar · International Conference on Information and Knowledge Management · 2020 · cited 454× - Machine Learning on Graphs: A Model and Comprehensive Taxonomy
Ines Chami, S. Abu-el-haija et al. · Journal of machine learning research · 2020 · cited 352× - A Time-Dependent SIR Model for COVID-19 With Undetectable Infected Persons
Yi-Cheng Chen, Ping-En Lu et al. · IEEE Transactions on Network Science and Engineering · 2020 · cited 232× - Karate Club: An API Oriented Open-Source Python Framework for Unsupervised Learning on Graphs
Benedek Rozemberczki, Oliver Kiss et al. · International Conference on Information and Knowledge Management · 2020 · cited 222×
Show all 10
- A Comprehensive Review of Community Detection in Graphs
Jiakang Li, Song-Ning Lai et al. · Neurocomputing · 2023 · cited 122× - Network Representation Learning: From Preprocessing, Feature Extraction to Node Embedding
Jing-Ya Zhou, Ling Liu et al. · ACM Computing Surveys · 2021 · cited 115× - Influence maximization in social networks using transfer learning via graph-based LSTM
Sanjay Kumar, Abhishek Mallik et al. · Expert systems with applications · 2022 · cited 110× - Twitch Gamers: a Dataset for Evaluating Proximity Preserving and Structural Role-based Node Embeddings
Benedek Rozemberczki, Rik Sarkar · arXiv.org · 2021 · cited 108× - Survey on graph embeddings and their applications to machine learning problems on graphs
I. Makarov, Dmitrii Kiselev et al. · PeerJ Computer Science · 2021 · cited 107×
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{rozemberczki2019gemsec,
title = {{GEMSEC}: Graph Embedding with Self Clustering},
author = {Rozemberczki, Benedek and Davies, Ryan and Sarkar, Rik and Sutton, Charles},
booktitle = {Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining},
year = {2019},
publisher = {ACM},
doi = {10.1145/3341161.3342890}
} APA
Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory
Rozemberczki, B., Davies, R., Sarkar, R., & Sutton, C. (2019). GEMSEC Facebook Page-Page Networks (Cumulative) [Data set]. https://doi.org/10.1145/3341161.3342890
MLA
Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.
Rozemberczki, Benedek, et al. GEMSEC Facebook Page-Page Networks (Cumulative). 2019, doi.org/10.1145/3341161.3342890.