Community Detection in Multiplex Networks
Abstract
A multiplex network models different modes of interaction among same-type entities. In this article we provide a taxonomy of community detection algorithms in multiplex networks. We characterize the different algorithms based on various properties and we discuss the type of communities detected by each method. We then provide an extensive experimental evaluation of the reviewed methods to answer three main questions: to what extent the evaluated methods are able to detect ground-truth communities, to what extent different methods produce similar community structures and to what extent the evaluated methods are scalable. One goal of this survey is to help scholars and practitioners to choose the right methods for the data and the task at hand, while also emphasizing when such choice is problematic.
Cite
@article{arxiv.1910.07646,
title = {Community Detection in Multiplex Networks},
author = {Matteo Magnani and Obaida Hanteer and Roberto Interdonato and Luca Rossi and Andrea Tagarelli},
journal= {arXiv preprint arXiv:1910.07646},
year = {2021}
}
Comments
55 pages. Accepted for publication on ACM Computing Surveys in a shorter version