Random walks and community detection in hypergraphs
Statistical Mechanics
2020-10-28 v1 Social and Information Networks
Dynamical Systems
Physics and Society
Abstract
We propose a one parameter family of random walk processes on hypergraphs, where a parameter biases the dynamics of the walker towards hyperedges of low or high cardinality. We show that for each value of the parameter the resulting process defines its own hypergraph projection on a weighted network. We then explore the differences between them by considering the community structure associated to each random walk process. To do so, we generalise the Markov stability framework to hypergraphs and test it on artificial and real-world hypergraphs.
Cite
@article{arxiv.2010.14355,
title = {Random walks and community detection in hypergraphs},
author = {Timoteo Carletti and Duccio Fanelli and Renaud Lambiotte},
journal= {arXiv preprint arXiv:2010.14355},
year = {2020}
}