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| Hauptverfasser: | , , , , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2405.04559 |
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| _version_ | 1866910438117081088 |
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| author | Battistella, Enzo English, Sean Green, Robert Joslyn, Cliff Lagoda, Evgeniya Magnan, Van Myers, Audun Nash, Evan D. Robinson, Michael |
| author_facet | Battistella, Enzo English, Sean Green, Robert Joslyn, Cliff Lagoda, Evgeniya Magnan, Van Myers, Audun Nash, Evan D. Robinson, Michael |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_04559 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Understanding High-Order Network Structure using Permissible Walks on Attributed Hypergraphs Battistella, Enzo English, Sean Green, Robert Joslyn, Cliff Lagoda, Evgeniya Magnan, Van Myers, Audun Nash, Evan D. Robinson, Michael Social and Information Networks Combinatorics 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. |
| title | Understanding High-Order Network Structure using Permissible Walks on Attributed Hypergraphs |
| topic | Social and Information Networks Combinatorics |
| url | https://arxiv.org/abs/2405.04559 |