Random walks and community detection in hypergraphs

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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.
Original languageEnglish
Article number015011
JournalJournal of Physics: Complexity
Issue number1
Publication statusPublished - 6 Apr 2021


  • hypergraphs
  • random walk
  • community detection
  • Higher-order networks
  • Random walks
  • Hypergraphs


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