Jester Joke Rating Network
A Jester Online Joke Recommender System (UC Berkeley) dataset of 73,521 nodes and 4,136,360 edges, collected by K. Goldberg et al. via Jester system. Each record contains directed: False, weighted: True, temporal: False. Bipartite user-joke rating network with continuous ratings from -10 to +10 — one of the earliest large-scale collaborative filtering datasets.. Suitable for recommender systems, collaborative filtering, continuous rating prediction.
Cite this dataset at
jester.echo.directory
Analytics
The full graph has 73,521 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
jester- Authors
- Goldberg, Ken; Roeder, Theresa; Gupta, Dhruv; Perkins, Chris
- Year
- 2001
- Source paper
- Eigentaste: A Constant Time Collaborative Filtering Algorithm
- DOI / arXiv
- 10.1023/A:1011419012209
- License
- CC BY-SA 2.0 Germany (as stated by KONECT) (LicenseRef-CC-BY-SA-2.0-DE)
- Records
- 73,521
- Nodes
- 73,521
- Edges
- 4,136,360
- Nodes are
- user / joke
- Edges are
- rating
- Attributes
- nodes have no attributes; edges have attributes
- Languages
- en
- Collected
- 2003 (2000s)
- Tasks
- Recommendation (ranking) inferred
From the graph: link prediction, community detection
Provenance
- Originally published at
- https://konect.cc/networks/jester2/ unverified
- Hosted copy
- Mirrored on echo.directory on 2026-10-02, 13.3 MB across 1 files. Checksums in MANIFEST.json.
Citations
Eigentaste: A Constant Time Collaborative Filtering Algorithm
Ken Goldberg, T. Roeder, Dhruv Gupta, Chris Perkins
Journal Article · Information retrieval (Boston) · 2001
Cited by
- High-Dimensional Statistics
M. Wainwright · 2019 · cited 698× - RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms
W. Zhao, Shanlei Mu et al. · International Conference on Information and Knowledge Management · 2020 · cited 662× - Making sense of recommendations
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C. Riquelme, G. Tucker et al. · International Conference on Learning Representations · 2018 · cited 407× - A recommender system based on collaborative filtering using ontology and dimensionality reduction techniques
M. Nilashi, O. Ibrahim et al. · Expert systems with applications · 2018 · cited 327×
Show all 10
- StarSpace: Embed All The Things!
Ledell Yu Wu, Adam Fisch et al. · AAAI Conference on Artificial Intelligence · 2017 · cited 259× - A Deep Latent Factor Model for High-Dimensional and Sparse Matrices in Recommender Systems
Di Wu, Xin Luo et al. · IEEE Transactions on Systems, Man & Cybernetics. Systems · 2019 · cited 209× - An L1-and-L2-Norm-Oriented Latent Factor Model for Recommender Systems
Di Wu, Ming-Sheng Shang et al. · IEEE Transactions on Neural Networks and Learning Systems · 2021 · cited 202× - Meta Matrix Factorization for Federated Rating Predictions
Yujie Lin, P. Ren et al. · Annual International ACM SIGIR Conference on Research and Development in Information Retrieval · 2019 · cited 170× - Evaluating Collaborative Filtering Recommender Algorithms: A Survey
M. Jalili, S. Ahmadian et al. · IEEE Access · 2018 · cited 166×
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}
}
@article{Goldberg_2001,
title = {Eigentaste: A Constant Time Collaborative Filtering Algorithm},
volume = {4},
issn = {1573-7659},
url = {http://dx.doi.org/10.1023/A:1011419012209},
doi = {10.1023/a:1011419012209},
number = {2},
journal = {Information Retrieval},
publisher = {Springer Science and Business Media LLC},
author = {Goldberg, Ken and Roeder, Theresa and Gupta, Dhruv and Perkins, Chris},
year = {2001},
month = July,
pages = {133–151}
} APA
Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory
Goldberg, K., Roeder, T., Gupta, D., & Perkins, C. (2001). Jester Joke Rating Network [Data set]. https://doi.org/10.1023/A:1011419012209
MLA
Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.
Goldberg, Ken, et al. Jester Joke Rating Network. 2001, doi.org/10.1023/A:1011419012209.