Cora Citation Network
A Cora machine learning paper database dataset of 23,166 nodes and 91,500 edges, collected by McCallum et al.. Each record contains directed: True, weighted: False. Classic citation network of machine learning papers — one of the most used benchmarks for graph neural network node classification.. Suitable for graph neural networks, node classification, citation network analysis.
Cite this dataset at
cora.echo.directory
Analytics
The full graph has 23,166 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
cora- Authors
- Šubelj, Lovro; Bajec, Marko
- Year
- 2013
- Source paper
- Model of complex networks based on citation dynamics
- DOI / arXiv
- 10.1145/2487788.2487987
- License
- CC BY-SA 2.0 Germany (as stated by KONECT) (LicenseRef-CC-BY-SA-2.0-DE)
- Records
- 23,166
- Nodes
- 23,166
- Edges
- 91,500 (directed)
- Nodes are
- paper
- Edges are
- citation
- Attributes
- nodes have attributes; edges have no attributes
- Languages
- en
- Collected
- 2000 (2000s)
- Tasks
- From the graph: link prediction, community detection
Provenance
- Originally published at
- https://konect.cc/networks/subelj_cora/ unverified
- Hosted copy
- Mirrored on echo.directory on 2026-10-16, 442.9 KB across 1 files. Checksums in MANIFEST.json.
Citations
Model of complex networks based on citation dynamics
Lovro Šubelj, M. Bajec
Journal Article · The Web Conference · 2013
Cited by
- Asymmetric Transitivity Preserving Graph Embedding
Mingdong Ou, Peng Cui et al. · Knowledge Discovery and Data Mining · 2016 · cited 1.3K× - Exploiting Edge Features in Graph Neural Networks.
Liyu Gong, Qiang Cheng · 2018 · cited 333× - Line Graph Neural Networks for Link Prediction
Lei Cai, Jundong Li et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence · 2020 · cited 307× - Nonparametric Bayesian inference of the microcanonical stochastic block model.
Tiago P. Peixoto · Physical Review E · 2016 · cited 210× - Linking the network centrality measures closeness and degree
T. Evans, Bingsheng Chen · Communications Physics · 2021 · cited 110×
Show all 10
- Predicting percolation thresholds in networks.
F. Radicchi · Physical review. E, Statistical, nonlinear, and soft matter physics · 2014 · cited 84× - Human information processing in complex networks
Christopher W. Lynn, Lia Papadopoulos et al. · Nature Physics · 2019 · cited 69× - A Broader Picture of Random-walk Based Graph Embedding
Zexi Huang, A. Silva et al. · Knowledge Discovery and Data Mining · 2021 · cited 67× - Node Representation Learning for Directed Graphs
Megha Khosla, Jurek Leonhardt et al. · ECML/PKDD · 2018 · cited 66× - A Comparative Study for Unsupervised Network Representation Learning
Megha Khosla, Vinay Setty et al. · IEEE Transactions on Knowledge and Data Engineering · 2019 · cited 62×
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{_ubelj_2013,
series = {WWW ’13},
title = {Model of complex networks based on citation dynamics},
url = {http://dx.doi.org/10.1145/2487788.2487987},
doi = {10.1145/2487788.2487987},
booktitle = {Proceedings of the 22nd International Conference on World Wide Web},
publisher = {ACM},
author = {Šubelj, Lovro and Bajec, Marko},
year = {2013},
month = May,
pages = {527–530},
collection = {WWW ’13}
} APA
Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory
Šubelj, L., & Bajec, M. (2013). Cora Citation Network [Data set]. https://doi.org/10.1145/2487788.2487987
MLA
Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.
Šubelj, Lovro, and Marko Bajec. Cora Citation Network. 2013, doi.org/10.1145/2487788.2487987.