The DOI matches its Crossref record; 28 of the 29 references it cites were found in a registry or an index.
Resolution limit in community detection
Open accessAbstract
Detecting community structure is fundamental for uncovering the links between structure and function in complex networks and for practical applications in many disciplines such as biology and sociology. A popular method now widely used relies on the optimization of a quantity called modularity, which is a quality index for a partition of a network into communities. We find that modularity optimization may fail to identify modules smaller than a scale which depends on the total size of the network and on the degree of interconnectedness of the modules, even in cases where modules are unambiguously defined. This finding is confirmed through several examples, both in artificial and in real social, biological, and technological networks, where we show that modularity optimization indeed does not resolve a large number of modules. A check of the modules obtained through modularity optimization is thus necessary, and we provide here key elements for the assessment of the reliability of this community detection method.
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“However, modularity-based graph clustering suffers a well-known resolution limit (Fortunato and Barthélemy, 2007), failing to find small clusters even when they are perfectly unambiguously defined.”
From Molecular Architecture of the Mouse Nervous System (2018) · cites this paper as Fortunato and Barthélemy, 2007
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
Statistical mechanics of complex networks
Albert, R., & Barabási, A.-L. (2002) · Reviews of Modern Physics · doi:10.1103/revmodphys.74.47 · Cited by 20,471
The Structure and Function of Complex Networks
Newman, M. E. J. (2003) · SIAM Review · doi:10.1137/s003614450342480 · Cited by 18,719
Community structure in social and biological networks
Girvan, M., & Newman, M. E. J. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.122653799 · Cited by 15,502
Complex networks: structure and dynamics
BOCCALETTI, S., LATORA, V, MORENO, Y., CHAVEZ, M., & HWANG, D. (2006) · Physics Reports · doi:10.1016/j.physrep.2005.10.009 · Cited by 11,010
Finding community structure in very large networks
Clauset, A., Newman, M. E. J., & Moore, C. (2004) · Physical Review E · doi:10.1103/physreve.70.066111 · Cited by 7,390
Network motifs: simple building blocks of complex networks.
Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., & Alon, U. (2002) · Science · doi:10.1126/science.298.5594.824 · Cited by 7,368
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
Hierarchical Organization of Modularity in Metabolic Networks
Ravasz, E., Somera, A. L., Mongru, D. A., Oltvai, Z. N., & Barabási, A.-L. (2002) · Science · doi:10.1126/science.1073374 · Cited by 4,224
Functional cartography of complex metabolic networks
Guimerà, R., & Nunes Amaral, L. A. (2005) · Nature · doi:10.1038/nature03288 · Cited by 3,983
From molecular to modular cell biology.
Hartwell, L. H., Hopfield, J. J., Leibler, S., & Murray, A. W. (1999) · Nature · doi:10.1038/35011540 · Cited by 3,632
The political blogosphere and the 2004 U.S. election: divided they blog
Adamic, L. A., & Glance, N. (2005) · Proceedings of the 3rd international workshop on Link discovery · doi:10.1145/1134271.1134277 · Cited by 2,619
Defining and identifying communities in networks
Radicchi, F., Castellano, C., Cecconi, F., Loreto, V., & Parisi, D. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0400054101 · Cited by 2,450
Detecting community structure in networks
Newman, M. E. J. (2004) · The European Physical Journal B · doi:10.1140/epjb/e2004-00124-y · Cited by 2,031
Dorogovtsev, S. N., & Mendes, J. F. F. (2003) · doi:10.1093/acprof:oso/9780198515906.001.0001 · Cited by 1,563
Community detection in complex networks using extremal optimization
Duch, J., & Arenas, À. (2005) · Physical Review E · doi:10.1103/physreve.72.027104 · Cited by 1,550
Evolution and Structure of the Internet
Pastor‐Satorras, R., & Vespignani, A. (2004) · Cambridge University Press eBooks · doi:10.1017/cbo9780511610905 · Cited by 1,302
Self-organization and identification of Web communities
Flake, G. W., Lawrence, S., Giles, C. L., & Coetzee, F. M. (2002) · Computer · doi:10.1109/2.989932 · Cited by 1,019
Modularity from fluctuations in random graphs and complex networks
Guimerà, R., Sales-Pardo, M., & Amaral, L. A. N. (2004) · Physical Review E · doi:10.1103/physreve.70.025101 · Cited by 894
Compartments revealed in food-web structure.
Krause, A. E., Frank, K. A., Mason, D. M., Ulanowicz, R. E., & Taylor, W. W. (2003) · Nature · doi:10.1038/nature02115 · Cited by 795
Identifying the role that animals play in their social networks
Lusseau, D., & Newman, M. E. J. (2004) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rsbl.2004.0225 · Cited by 752
Subnetwork hierarchies of biochemical pathways
Holme, P., Huss, M., & Jeong, H. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg033 · Cited by 369
Sexual mixing patterns in the spread of gonococcal and chlamydial infections.
Aral, S. O., Hughes, J. P., Stoner, B. P., Whittington, W. L. H., Handsfield, H. H., Anderson, R. M., & Holmes, K. K. (1999) · American Journal of Public Health · doi:10.2105/ajph.89.6.825 · Cited by 271
The effect of size heterogeneity on community identification in complex networks
Danon, L., Dı́az-Guilera, A., & Arenas, À. (2006) · Journal of Statistical Mechanics Theory and Experiment · doi:10.1088/1742-5468/2006/11/p11010 · Cited by 234
Pimm, S. L. (1979) · Theoretical Population Biology · doi:10.1016/0040-5809(79)90010-8 · Cited by 227
Modularity and Extreme Edges of the Internet
Eriksen, K. A., Simonsen, I., Maslov, S., & Sneppen, K. (2003) · Physical Review Letters · doi:10.1103/physrevlett.90.148701 · Cited by 213
Hierarchical thinking in network biology: the unbiased modularization of biochemical networks
Papin, J. A., Reed, J. L., & Palsson, B. Ø. (2004) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2004.10.001 · Cited by 197
Local modularity measure for network clusterizations
Muff, S., Rao, F. V., & Caflisch, A. (2005) · Physical Review E · doi:10.1103/physreve.72.056107 · Cited by 160
Sexual Mixing Patterns of Patients Attending Sexually Transmitted Diseases Clinics
Garnett, G. P., Hughes, J. P., Anderson, R. M., Stoner, B. P., ARAL, S. O., Whittington, W. L. H., Handsfield, H. H., & Holmes, K. K. (1996) · Sexually Transmitted Diseases · doi:10.1097/00007435-199605000-00015 · Cited by 140
Research works printed but not linked: 5
- L Danon, A Díaz-Guilera, J Duch, A Arenas J Stat Mech, P09008. (2005).
- MEJ Newman, M Girvan Phys Rev E 69, 026113. (2004).
- MEJ Newman Phys Rev E 69, 066133. (2004).
- J Reichardt, S Bornholdt Phys Rev E 74, 016110. (2006).
- J Reichardt S Bornholdt arXiv:cond-mat/0606220. (2006). · arXiv
Cited by
Sorted by citations
Fast unfolding of communities in large networks
Blondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008) · Journal of Statistical Mechanics: Theory and Experiment · doi:10.1088/1742-5468/2008/10/p10008 · Cited by 21,424
Fortunato, S. (2010) · Physics Reports · doi:10.1016/j.physrep.2009.11.002 · Cited by 11,293
Self-citationFrom Louvain to Leiden: guaranteeing well-connected communities
Traag, V. A., Waltman, L., & van Eck, N. J. (2019) · Scientific Reports · doi:10.1038/s41598-019-41695-z · Cited by 5,635
An Information Flow Model for Conflict and Fission in Small Groups
Zachary, W. W. (1977) · Journal of Anthropological Research · doi:10.1086/jar.33.4.3629752 · Cited by 4,709
Benchmark graphs for testing community detection algorithms
Lancichinetti, A., Fortunato, S., & Radicchi, F. (2008) · Physical Review E · doi:10.1103/physreve.78.046110 · Cited by 3,058
Self-citation
Metadata
- Authors
- Fortunato, S., & Barthélemy, M.
- Affiliations
- Institute for Scientific Interchange (IT)
- Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR)
- Corresponding author
- Barthélemy, Marc
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2007-01-02
- Volume
- 104
- Issue
- 1
- Pages
- 36-41
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC1765466
- OpenAlex
- W2128366083
- Cited by
- 3,024
- References
- 29
- Citations by year
- 2026: 93 · 2025: 134 · 2024: 126 · 2023: 112 · 2022: 150 · 2021: 154 · 2020: 186 · 2019: 209 · 2018: 241 · 2017: 195 · 2016: 198 · 2015: 195 · 2014: 215 · 2013: 193 · 2012: 165
- FWCI
- 40.39
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- CERN Document Server (European Organization for Nuclear Research) (submittedVersion)
- arXiv (Cornell University)
- 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, resolution limit, modularity optimization, network partitioning, complex networks, module reliability, social networks, biological networks, technological networks
- MeSH terms
- Animals, Humans, Models, Theoretical, Community Networks
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
