LinkRank: Finding communities in directed networks
Youngdo Kim, Seung-Woo Son, and Hawoong Jeong

TL;DR
This paper introduces LinkRank, a new modularity measure for directed networks, enabling effective community detection by extending undirected modularity concepts and providing a benchmark model for validation.
Contribution
The paper proposes LinkRank, a novel link-based modularity measure for directed networks, and demonstrates its effectiveness with a new benchmark network model.
Findings
LinkRank generalizes modularity for directed networks
The method effectively detects communities in citation networks
A benchmark network model supports validation of the approach
Abstract
To identify communities in directed networks, we propose a generalized form of modularity in directed networks by introducing a new quantity LinkRank, which can be considered as the PageRank of links. This generalization is consistent with the original modularity in undirected networks and the modularity optimization methods developed for undirected networks can be directly applied to directed networks by optimizing our new modularity. Also, a model network, which can be used as a benchmark network in further community studies, is proposed to verify our method. Our method is supposed to find communities effectively in citation- or reference-based directed networks.
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