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 adapt the Markov stability framework to hypergraphs and test it on artificial and real-world hypergraphs.
Random walks and community detection in hypergraphs / Carletti, T; Fanelli, D; Lambiotte, R. - In: JOURNAL OF PHYSICS. COMPLEXITY. - ISSN 2632-072X. - STAMPA. - 2:(2021), pp. 015011-015011. [10.1088/2632-072X/abe27e]
Random walks and community detection in hypergraphs
Carletti, T;Fanelli, D;
2021
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 adapt the Markov stability framework to hypergraphs and test it on artificial and real-world hypergraphs.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.