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robin

Available on CRAN https://CRAN.R-project.org/package=robin

ROBIN (ROBustness In Network) is an R package for the validation of community detection. It has a double aim: it studies the robustness of a community detection algorithm and it compares the robustness of two community detection algorithms.

The package implements a methodology that detects if the community structure found by a detection algorithm is statistically significant or is a result of chance, merely due to edge positions in the network.

The package:
  1. Examine the robustness of a community detection algorithm against random perturbations of the original graph

  2. Tests the statistical difference between the stability measure curves created

  3. Makes a comparison between different community detection algorithms to choose the one that better fits the network of interest

  4. Gives a graphical interactive representation


Example 1: "Robustness of a community detection algorithm"

my_network <- system.file("example/football.gml", package="robin")
graph <- prepGraph(file=my_network, file.format="gml")
graphRandom <- random(graph=graph)
proc <- robinRobust(graph=graph, graphRandom=graphRandom, measure="vi", method="louvain", type="independent")               
plotRobin(graph=graph, model1=proc$Mean, model2=proc$MeanRandom, legend=c("real data", "null model"))
#For the testing:
robinFDATest(graph=graph, model1=proc$Mean, model2=proc$MeanRandom)
robinGPTest(model1=proc$Mean, model2=proc$MeanRandom)

Example 2: "Comparison of two community detection algorithms"

my_network <- system.file("example/football.gml", package="robin")
graph <- prepGraph(file=my_network, file.format="gml")
comp <- robinCompare(graph=graph, method1="fastGreedy", method2="louvain", measure="vi", type="independent")                
plotRobin(graph=graph, model1=comp$Mean1, model2=comp$Mean2, legend=c("fastGreedy", "louvain"), title="FastGreedy vs Louvain")
#For the testing:
robinFDATest(graph=graph, model1=comp$Mean1, model2=comp$Mean2)
robinGPTest(model1=comp$Mean1, model2=comp$Mean2)

Reference

ROBustness In Network (robin): an R package for Comparison and Validation of communities Valeria Policastro, Dario Righelli, Annamaria Carissimo, Luisa Cutillo, Italia De Feis. The R Journal (2021) https://journal.r-project.org/archive/2021/RJ-2021-040/index.html

License

Copyright (c) 2019 V. Policastro, A. Carissimo, L. Cutillo, I. De Feis and D. Righelli.

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Install

install.packages('robin')

Monthly Downloads

23,752

Version

1.1.2

License

MIT + file LICENSE

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Maintainer

Valeria Policastro

Last Published

January 31st, 2024

Functions in robin (1.1.2)

prepGraph

prepGraph
createITPSplineResult

createITPSplineResult
plotGraph

plotGraph
methodCommunity

methodCommunity
plotRobin

plotRobin
membershipCommunities

membershipCommunities
plotComm

plotComm
random

random
robinCompareFast

robinCompareFast
robinCompare

robinCompare
robinRobust

robinRobust
robinAUC

robinAUC
robinGPTest

robinGPTest
robinFDATest

robinFDATest
rewireOnl

rewireOnl
rewireCompl

rewireCompl