Citing pymocd¶

The paper to cite for pymocd is the HP-MOCD paper, Santos et al. (2025), published in Social Network Analysis and Mining (doi:10.1007/s13278-025-01519-7): the repository README asks anyone who uses any of the library's algorithms in research to cite it. If your work uses one of the re-implemented baselines, also cite the paper that defines that method; the entries are listed below. This page also explains what to do for RIMPSO, whose paper is not yet published, and for the software itself.

The pymocd paper¶

How to cite

Santos, G. O., Vieira, L. S., Rossetti, G., Ferreira, C. H. G., & Moreira, G. J. P. (2025). A high-performance evolutionary multiobjective community detection algorithm. Social Network Analysis and Mining, 15(1), 110. https://doi.org/10.1007/s13278-025-01519-7

@article{Santos2025,
  author    = {Santos, Guilherme O. and Vieira, Lucas S. and Rossetti, Giulio and Ferreira, Carlos H. G. and Moreira, Gladston J. P.},
  title     = {A high-performance evolutionary multiobjective community detection algorithm},
  journal   = {Social Network Analysis and Mining},
  year      = {2025},
  volume    = {15},
  number    = {1},
  pages     = {110},
  doi       = {10.1007/s13278-025-01519-7},
  url       = {https://doi.org/10.1007/s13278-025-01519-7},
  issn      = {1869-5469},
  date      = {2025-11-18}
}

This is the entry from the repository README. Every field agrees with the Crossref record of the DOI: the authors, title, journal, volume 15, issue 1, the electronic ISSN and the online publication date of 18 November 2025. The value in pages is the article number: Crossref records 110 as the article number and gives no page range.

Some of the same authors have also published two short Portuguese-language summaries of this paper, listed on the Publications page. Both refer readers to the journal paper for the full results; cite the journal paper.

Report the version you used¶

Defaults, selection rules and detector names have changed between releases (see the Changelog), so state the pymocd version next to the citation. The installed version is reported by the package metadata. This site was built with:

from importlib.metadata import version

print(version("pymocd"))

6.1.1

Some detectors, HP-MOCD among them, can return a different partition on each call; see Performance and reproducibility for which detectors are deterministic.

Citing RIMPSO¶

RIMPSO, the library's recommended default detector, has not been published yet: the repository cites it as Santos, in preparation (2026), and there is no DOI or BibTeX record for it. Until its paper appears, cite the pymocd paper above, as the README asks for any of the library's algorithms, refer to the method as RIMPSO, and give the pymocd version you used. The method itself is described on the RIMPSO page.

Citing a re-implemented baseline¶

If you use a re-implemented baseline, also cite its original paper. These detectors are ports written from the papers, and each algorithm page lists where the port deliberately diverges from its paper. When you report results obtained with them, say that you used the pymocd implementation.

Method	Entry points	Original paper	DOI
CDRME	`cdrme`	Dabaghi-Zarandi, Afkhami & Ashoori (2025), Journal of Network and Computer Applications 234, 104070	10.1016/j.jnca.2024.104070
MMCoMO	`mmcomo`, `mmcomo_fronts`	Zhang, Yang, Yang & Zhang (2023), IEEE Computational Intelligence Magazine 18(3), 69–86	10.1109/MCI.2023.3277773
NSGA-III-CCM	`ccm`, `ccm_fronts`	Shaik, Ravi & Deb (2021), SN Computer Science 2(1), article 1	10.1007/s42979-020-00382-x
NSGA-III-KRM	`krm`, `krm_fronts`	Shaik, Ravi & Deb (2021), same paper as NSGA-III-CCM	10.1007/s42979-020-00382-x
GDPSO	`gdpso`	Cai, Gong, Ma, Ruan, Yuan & Jiao (2015), Information Sciences 316, 503–516	10.1016/j.ins.2014.09.041
Shi-MOCD	`mocd_q`, `mocd_d`	Shi, Yan, Cai & Wu (2012), Applied Soft Computing 12(2), 850–859	10.1016/j.asoc.2011.10.005
MOGA-Net	`moga_net`, `moga_net_fronts`	Pizzuti (2012), IEEE Transactions on Evolutionary Computation 16(3), 418–430	10.1109/TEVC.2011.2161090

Volumes, issues, pages and article numbers follow the Crossref record of each DOI. The NSGA-III-CCM and NSGA-III-KRM paper was published online in November 2020 and appeared in the 2021 volume, which is why its BibTeX entry below says 2020. The MOGA-Net module README also cites Pizzuti's earlier conference paper at ICTAI 2009 (doi:10.1109/ICTAI.2009.58), which defines the operators, and treats the 2012 journal paper as the authority for the parameters.

The entries below are the publisher records returned by doi.org content negotiation for each DOI, laid out one field per line, with two changes. The GDPSO and MOGA-Net (2012) entries give the month as sep and jun, because doi.org writes Sept and June, which are not BibTeX month macros. The NSGA-III-CCM and NSGA-III-KRM entry adds a pages field, which the doi.org record leaves out; its value is the article number 1, from Crossref.

BibTeX: CDRME (Dabaghi-Zarandi et al., 2025)

@article{Dabaghi_Zarandi_2025,
  title     = {Community Detection method based on Random walk and Multi objective Evolutionary algorithm in complex networks},
  volume    = {234},
  ISSN      = {1084-8045},
  url       = {http://dx.doi.org/10.1016/j.jnca.2024.104070},
  DOI       = {10.1016/j.jnca.2024.104070},
  journal   = {Journal of Network and Computer Applications},
  publisher = {Elsevier BV},
  author    = {Dabaghi-Zarandi, Fahimeh and Afkhami, Mohammad Mehdi and Ashoori, Mohammad Hossein},
  year      = {2025},
  month     = Feb,
  pages     = {104070}
}

BibTeX: MMCoMO (Zhang et al., 2023)

@article{Zhang_2023,
  title     = {A Macro-Micro Population-Based Co-Evolutionary Multi-Objective Algorithm for Community Detection in Complex Networks [Research Frontier]},
  volume    = {18},
  ISSN      = {1556-6048},
  url       = {http://dx.doi.org/10.1109/MCI.2023.3277773},
  DOI       = {10.1109/mci.2023.3277773},
  number    = {3},
  journal   = {IEEE Computational Intelligence Magazine},
  publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
  author    = {Zhang, Lei and Yang, Haipeng and Yang, Shangshang and Zhang, Xingyi},
  year      = {2023},
  month     = Aug,
  pages     = {69–86}
}

BibTeX: NSGA-III-CCM and NSGA-III-KRM (Shaik et al., 2021)

@article{Shaik_2020,
  title     = {Evolutionary Multi-Objective Optimization Algorithm for Community Detection in Complex Social Networks},
  volume    = {2},
  ISSN      = {2661-8907},
  url       = {http://dx.doi.org/10.1007/s42979-020-00382-x},
  DOI       = {10.1007/s42979-020-00382-x},
  number    = {1},
  journal   = {SN Computer Science},
  publisher = {Springer Science and Business Media LLC},
  author    = {Shaik, Tanveerulhuq and Ravi, Vadlamani and Deb, Kalyanmoy},
  year      = {2020},
  month     = Nov,
  pages     = {1}
}

BibTeX: GDPSO (Cai et al., 2015)

@article{Cai_2015,
  title     = {Greedy discrete particle swarm optimization for large-scale social network clustering},
  volume    = {316},
  ISSN      = {0020-0255},
  url       = {http://dx.doi.org/10.1016/j.ins.2014.09.041},
  DOI       = {10.1016/j.ins.2014.09.041},
  journal   = {Information Sciences},
  publisher = {Elsevier BV},
  author    = {Cai, Qing and Gong, Maoguo and Ma, Lijia and Ruan, Shasha and Yuan, Fuyan and Jiao, Licheng},
  year      = {2015},
  month     = sep,
  pages     = {503–516}
}

BibTeX: Shi-MOCD (Shi et al., 2012)

@article{Shi_2012,
  title     = {Multi-objective community detection in complex networks},
  volume    = {12},
  ISSN      = {1568-4946},
  url       = {http://dx.doi.org/10.1016/j.asoc.2011.10.005},
  DOI       = {10.1016/j.asoc.2011.10.005},
  number    = {2},
  journal   = {Applied Soft Computing},
  publisher = {Elsevier BV},
  author    = {Shi, Chuan and Yan, Zhenyu and Cai, Yanan and Wu, Bin},
  year      = {2012},
  month     = Feb,
  pages     = {850–859}
}

BibTeX: MOGA-Net (Pizzuti, 2012)

@article{Pizzuti_2012,
  title     = {A Multiobjective Genetic Algorithm to Find Communities in Complex Networks},
  volume    = {16},
  ISSN      = {1941-0026},
  url       = {http://dx.doi.org/10.1109/TEVC.2011.2161090},
  DOI       = {10.1109/tevc.2011.2161090},
  number    = {3},
  journal   = {IEEE Transactions on Evolutionary Computation},
  publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
  author    = {Pizzuti, Clara},
  year      = {2012},
  month     = jun,
  pages     = {418–430}
}

BibTeX: MOGA-Net operators (Pizzuti, 2009)

@inproceedings{Pizzuti_2009,
  title     = {A Multi-objective Genetic Algorithm for Community Detection in Networks},
  url       = {http://dx.doi.org/10.1109/ICTAI.2009.58},
  DOI       = {10.1109/ictai.2009.58},
  booktitle = {2009 21st IEEE International Conference on Tools with Artificial Intelligence},
  publisher = {IEEE},
  author    = {Pizzuti, Clara},
  year      = {2009},
  month     = Nov,
  pages     = {379–386}
}

Citing the software¶

The repository root contains a CITATION.cff file in version 1.2.0 of the Citation File Format. It describes the software and names the pymocd paper above as its preferred citation. GitHub reads the file from the default branch and adds a Cite this repository link to the right sidebar of the repository page, which exports the citation as APA or BibTeX. Because the file sets a preferred citation, that link gives the pymocd paper, not the software.

No release has a DOI yet, so there is no archived, citable copy of the software. Cite the pymocd paper. If a venue also asks for a software reference, CITATION.cff records the following:

Title: pymocd
Author: Guilherme O. Santos, as in pyproject.toml
Version: 6.1.1, released on 1 November 2026, the release the file was written for. If you used another version, give the one printed by version("pymocd") above.
Repository: https://github.com/csilab-ufop/pymocd
Documentation: https://csilab.ufop.br/pymocd/
License: GPL-3.0-or-later

The package itself is published on PyPI as pymocd.