clustAnalytics: An R Package for Assessing Stability and Significance of Communities in Networks

Martí Renedo-Mirambell; Argimiro Arratia

doi:10.32614/RJ-2023-057

clustAnalytics: An R Package for Assessing Stability and Significance of Communities in Networks

This paper introduces the R package clustAnalytics, which comprises a set of criteria for assessing the significance and stability of communities in networks found by any clustering algorithm. clustAnalytics works with graphs of class igraph from the R-package igraph, extended to handle weighted and/or directed graphs. clustAnalytics provides a set of community scoring functions, and methods to systematically compare their values to those of a suitable null model, which are of use when testing for cluster significance. It also provides a non parametric bootstrap method combined with similarity metrics derived from information theory and combinatorics, useful when testing for cluster stability, as well as a method to synthetically generate a weighted network with a ground truth community structure based on the preferential attachment model construction, producing networks with communities and scale-free degree distribution.

0.1 Supplementary materials

Supplementary materials are available in addition to this article. It can be downloaded at RJ-2023-057.zip

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For attribution, please cite this work as

Renedo-Mirambell & Arratia, "clustAnalytics: An R Package for Assessing Stability and Significance of Communities in Networks", The R Journal, 2023

BibTeX citation

@article{RJ-2023-057,
  author = {Renedo-Mirambell, Martí and Arratia, Argimiro},
  title = {clustAnalytics: An R Package for Assessing Stability and Significance of Communities in Networks},
  journal = {The R Journal},
  year = {2023},
  note = {https://doi.org/10.32614/RJ-2023-057},
  doi = {10.32614/RJ-2023-057},
  volume = {15},
  issue = {2},
  issn = {2073-4859},
  pages = {134-144}
}