Understanding High-Order Network Structure using Permissible Walks on Attributed Hypergraphs

Hypergraphs have been a recent focus of study in mathematical data science as a tool to understand complex networks with high-order connections. One question of particular relevance is how to leverage information carried in hypergraph attributions when doing walk-based techniques. In this work, we f...

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Veröffentlicht in:arXiv.org 2024-05
Hauptverfasser: Battistella, Enzo, English, Sean, Green, Robert, Joslyn, Cliff, Lagoda, Evgeniya, Magnan, Van, Myers, Audun, Nash, Evan D, Robinson, Michael
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Sprache:eng
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Zusammenfassung:Hypergraphs have been a recent focus of study in mathematical data science as a tool to understand complex networks with high-order connections. One question of particular relevance is how to leverage information carried in hypergraph attributions when doing walk-based techniques. In this work, we focus on a new generalization of a walk in a network that recovers previous approaches and allows for a description of permissible walks in hypergraphs. Permissible walk graphs are constructed by intersecting the attributed \(s\)-line graph of a hypergraph with a relation respecting graph. The attribution of the hypergraph's line graph commonly carries over information from categorical and temporal attributions of the original hypergraph. To demonstrate this approach on a temporally attributed example, we apply our framework to a Reddit data set composed of hyperedges as threads and authors as nodes where post times are tracked.
ISSN:2331-8422