ig.degree.betweenness

An R package for the implementation of the "Smith-Pittman" (2024) community detection algorithm. Also known as the node degree+edge betweenness algorithm. Compatible with the igraph ecosystem.

• For the Python implementation, see ig_degree_betweenness_py.
• For the C implementation, see ig_degree_betweenness_c

Algorithm Visualizations

How the Smith-Pittman algorithm works:

Installing this package

To install the stable release of this package from CRAN run:

install.packages("ig.degree.betweenness")

To install the development version of this package run:

# install.packages("devtools")
devtools::install_github("benyamindsmith/ig.degree.betweenness")

Sample Usage

Applying the node degree+edge betweenness algorithm can be done by making use of the cluster_degree_betweenness().

An example of using the code is:

library(igraphdata)
library(ig.degree.betweenness)

data("karate")

sp <- cluster_degree_betweenness(karate)
plot(
sp,
karate,
main= "Node degree+edge betweenness clustering"
)

Citation

To cite package ‘ig.degree.betweenness’ in publications use:

Smith, Pittman, and Xu (2024). Centrality in Collaboration: A Novel Algorithm for Social Partitioning Gradients in Community Detection for Multiple Oncology Clinical Trial Enrollments arXiv:2411.01394.

A BibTeX entry for LaTeX users is

@Misc{Smith_Pittman_Xu_2024,
    title = {Centrality in Collaboration: A Novel Algorithm for Social Partitioning Gradients in Community Detection for Multiple Oncology Clinical Trial Enrollments},
    author = {Benjamin Smith and Tyler Pittman and Wei Xu},
    year = {2024},
    month = {Nov},
    note = {arXiv:2411.01394},
    url = {https://arxiv.org/abs/2411.01394},
  }