The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Overlapping community detection using Bayesian non-negative matrix factorization
Abstract
Identifying overlapping communities in networks is a challenging task. In this work we present a probabilistic approach to community detection that utilizes a Bayesian non-negative matrix factorization model to extract overlapping modules from a network. The scheme has the advantage of soft-partitioning solutions, assignment of node participation scores to modules, and an intuitive foundation. We present the performance of the method against a variety of benchmark problems and compare and contrast it to several other algorithms for community detection.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Finding and evaluating community structure in networks
Newman, M. E. J., & Girvan, M. (2004) · Physical Review E · doi:10.1103/physreve.69.026113 · Cited by 13,931
Modularity and community structure in networks
Newman, M. E. J. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601602103 · Cited by 12,256
Fortunato, S. (2010) · Physics Reports · doi:10.1016/j.physrep.2009.11.002 · Cited by 11,293
Newman, M. (2010) · doi:10.1093/acprof:oso/9780199206650.001.0001 · Cited by 6,595
Uncovering the overlapping community structure of complex networks in nature and society
Palla, G., Derényi, I., Farkas, I., & Vicsek, T. (2005) · Nature · doi:10.1038/nature03607 · Cited by 5,373
The interaction of TIGIT with PVR and PVRL2 inhibits human NK cell cytotoxicity
Stanietsky, N., Simic, H., Arapovic, J., Toporik, A., Levy, O., Novik, A., Levine, Z., Beiman, M., Dassa, L., Achdout, H., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0903474106 · Cited by 3,524
Resolution limit in community detection
Fortunato, S., & Barthélemy, M. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0605965104 · Cited by 3,024
Bernardo, J. M., & Smith, A. F. M. (1994) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316870 · Cited by 2,178
Mackay, D. J. C. (1995) · Network Computation in Neural Systems · doi:10.1088/0954-898x/6/3/011 · Cited by 915
Cited by
Community detection in networks: A multidisciplinary review
Javed, M. A., Younis, M. S., Latif, S., Qadir, J., & Baig, A. (2018) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2018.02.011 · Cited by 499
Efficient and principled method for detecting communities in networks
Ball, B., Karrer, B., & Newman, M. E. J. (2011) · Physical Review E · doi:10.1103/physreve.84.036103 · Cited by 386
Towards Linear Time Overlapping Community Detection in Social Networks
Xie, J., & Szymanski, B. K. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-30220-6_3 · Cited by 280
Inferring social network structure in ecological systems from spatio-temporal data streams
Psorakis, I., Roberts, S. J., Rezek, I., & Sheldon, B. C. (2012) · Journal of The Royal Society Interface · doi:10.1098/rsif.2012.0223 · Cited by 171
Self-citation
Metadata
- Authors
- Psorakis, I., Roberts, S., Ebden, M., & Sheldon, B.
- Venue
- Physical Review E
- Publisher
- American Physical Society (APS)
- Published
- 2011-06-22
- Volume
- 83
- Issue
- 6
- Pages
- 066114-066114
- ISSN
- 1539-3755 (ISSN-L)
- 1550-2376
- OpenAlex
- W2050601254
- Cited by
- 399
- References
- 9
- FWCI
- 17.43
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Overlapping community detection using Bayesian non-negative matrix factorization. https://app.cochat.ai/papers/10.1103/physreve.83.066114
- The paper
- Psorakis, I., Roberts, S., Ebden, M., & Sheldon, B. (2011). Overlapping community detection using Bayesian non-negative matrix factorization. Physical Review E. https://doi.org/10.1103/physreve.83.066114
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
