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Cited by 2,086Complex Network Analysis TechniquesAdvanced Clustering Algorithms ResearchBioinformatics and Genomic Networks

Community detection in networks: a user guide

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Fortunato, Santo, Hric, Darko·2016·Physics Reports
DOI 10.1016/j.physrep.2016.09.002
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  • Popular methods for community detection in structural brain networks include the Louvain algorithm and stochastic block models.

    “Popular methods for community detection in structural brain networks include the Louvain algorithm and stochastic block models, though determining best practices around the utilization of these and other approaches remain an active topic of research (Fortunato and Hric, 2016).”

    From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Fortunato and Hric, 2016

    The Methods section (p. 22) describes popular community-detection algorithms, and the paper discusses both the Louvain method (p. 30) and stochastic block models (p. 37). The Introduction (p. 2) also says there are no clear-cut guidelines for comparing methods. These passages do not establish that Louvain and stochastic block models are popular specifically for structural brain networks. (LLM, conf=0.86)

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Authors
Fortunato, S., & Hric, D.
Affiliations
  • Indiana University Bloomington (US)
  • Aalto University (FI)
Corresponding author
Fortunato, Santo
ORCID
Fortunato, Santo
Venue
Physics Reports
Publisher
Elsevier BV
Published
2016-11
Volume
659
Pages
1-44
ISSN
0370-1573 (ISSN-L)
DOI
10.1016/j.physrep.2016.09.002
OpenAlex
W2951271819
Cited by
2,086
References
9
Citations by year
2026: 131 · 2025: 218 · 2024: 193 · 2023: 185 · 2022: 218 · 2021: 239 · 2020: 287 · 2019: 293 · 2018: 201 · 2017: 111 · 2016: 8 · 2015: 2
FWCI
107.17
Type
journal article
Language
en
Open access
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Physics Reports (publishedVersion)
  • arXiv (Cornell University) (acceptedVersion)
  • arXiv (Cornell University) (cc-by)
Funders
MULTIPLEX (317532)
Topics
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
  • Physical Sciences › Computer Science › Artificial Intelligence › Advanced Clustering Algorithms Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Keywords
community detection, network clustering, community structure, community definition, clustering algorithm comparison, network science

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