README.md

ig.degree.betweenness

An R package for the implementation of the "Smith-Pittman" (2024) community detection algorithm. Compatible with the igraph ecosystem.

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 Smith-Pittman 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= "Smith-Pittman Clustering"
)

Limitations

The present limitations of using this algorithm is that graphs are required to be labeled for the operations to work. For unlabeled graphs, graphs can be prepared with the prep_unlabled_graph() function.

Example:

library(igraph)
library(igraphdata)
library(ig.degree.betweenness)
data("UKfaculty")
# Making graph undirected so it looks nicer when its plotted
uk_faculty <- prep_unlabeled_graph(UKfaculty) |>
  as.undirected()

ndb <- cluster_degree_betweenness(uk_faculty)

plot(
ndb,
uk_faculty,
main= "Smith-Pittman Clustering for UK Faculty"
)