ROBustness In Network (robin): an R package for Comparison and Validation of communities

TL;DR

Robin is an R package designed to evaluate the statistical robustness and compare different community detection algorithms in network analysis, aiding in selecting the most reliable method.

Contribution

The paper introduces robin, an R package that assesses the significance and compares community detection algorithms, addressing a gap in validation methods for network communities.

Findings

Robin effectively detects statistically significant community structures.

The package enables comparison of algorithms to identify the best fit.

Application on the football dataset demonstrates practical utility.

Abstract

In network analysis, many community detection algorithms have been developed, however, their implementation leaves unaddressed the question of the statistical validation of the results. Here we present robin(ROBustness In Network), an R package to assess the robustness of the community structure of a network found by one or more methods to give indications about their reliability. The procedure initially detects if the community structure found by a set of algorithms is statistically significant and then compares two selected detection algorithms on the same graph to choose the one that better fits the network of interest. We demonstrate the use of our package on the American College Football benchmark dataset.