# HyperNetX: A Python package for modeling complex network data as hypergraphs

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/hypernetx-a-python-package-for-modeling-complex-network-data-as-hypergraphs/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Brenda Praggastis,Sinan G. Aksoy,Dustin Arendt,Mark Bonicillo,Cliff Joslyn,Emilie Purvine,Madelyn Shapiro,Ji Young Yun |
| Citations | 1 |
| DOI | 10.48550/arxiv.2310.11626 |
| Fields | Computer Science,Physics and Astronomy,Psychology |
| Open Access | true |
| OA Status | green |
| OA URL | https://arxiv.org/pdf/2310.11626 |
| OpenAlex ID | https://openalex.org/W4387800346 |
| Type | preprint |
| Year | 2023 |

## Paper authors

- [Ji Young Yun](https://scholariq.org/researchers/ji-young-yun/)

## Paper journal

- [arXiv (Cornell University)](https://scholariq.org/journals/arxiv-cornell-university/)

## Paper primary topic

- [Complex Network Analysis Techniques](https://scholariq.org/topics/complex-network-analysis-techniques/)

## Paper topics

- [Complex Network Analysis Techniques](https://scholariq.org/topics/complex-network-analysis-techniques/)
- [Data Visualization and Analytics](https://scholariq.org/topics/data-visualization-and-analytics/)
- [Mental Health Research Topics](https://scholariq.org/topics/mental-health-research-topics/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.