Entropy-based random models for hypergraphs
Network science has traditionally focused on pairwise relationships while disregarding many-body interactions. Hypergraphs are promising mathematical objects for the description of the latter ones. Here, we propose null models to analyse hypergraphs that generalise the classical Erdös-Rényi and Conf...
| 主要な著者: | , , , |
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| フォーマット: | Internet publication |
| 言語: | English |
| 出版事項: |
2022
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| 要約: | Network science has traditionally focused on pairwise relationships while disregarding many-body interactions. Hypergraphs are promising mathematical objects for the description of the latter ones. Here, we propose null models to analyse hypergraphs that generalise the classical Erdös-Rényi and Configuration Model by randomising incidence matrices in a constrained fashion. After discussing them, we extend the definition of several network quantities to hypergraphs, derive their expected values and compare them with empirical ones, to detect significant deviations from random behaviours. |
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