https://github.com/adityalab/uva-hypergraph
Anonymized UVA Contact Networks in Hypergraph
https://github.com/adityalab/uva-hypergraph
Last synced: 28 days ago
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Anonymized UVA Contact Networks in Hypergraph
- Host: GitHub
- URL: https://github.com/adityalab/uva-hypergraph
- Owner: AdityaLab
- License: mit
- Created: 2024-01-10T19:46:11.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-23T13:08:19.000Z (about 1 year ago)
- Last Synced: 2024-04-23T20:35:01.502Z (about 1 year ago)
- Size: 8.95 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# [SDM 2024] UVA-Hypergraph dataset
Anonymized UVA Contact Networks in Hypergraph
## Publication
H2ABM: Heterogeneous Agent-based Model on Hypergraphs to Capture Group Interactions.
Authors: Vivek Anand*, Jiaming Cui*, Jack Heavey, Anil Vullikanti, B. Aditya Prakash
*Equal contribution
Venue: SDM 2024
Link to the paper: https://sites.cc.gatech.edu/~jcui75/papers/h2abm-sdm24.pdf
Link to the code: https://github.com/AdityaLab/H2ABM
## Dataset
The dataset is at `data` folder. Each day.txt contains the co-location network for one day.
There are 5 columns in each txt file
```
person1,person2,start_time,end_time,location
```
Each row is one record of the co-location data on that day. It means [person1] and [person2] are at [location] from [start_time] to [end_time]
There are two kinds of person: patients (with id [MRN_]) and healthcare workers (with id [HCW_])
The [start_time] and [end_time] are in seconds. Numbers starting from 12:00 am.
## Cite our work
If you find our work useful, please cite our work:
- Vivek Anand*, Jiaming Cui*, Jack Heavey, Anil Vullikanti, B. Aditya Prakash. H2ABM: Heterogeneous Agent-based Model on Hypergraphs to Capture Group Interactions. SDM 2024.
```
@inproceedings{anand2024h2abm,
title={},
author={Anand, Vivek and Cui, Jiaming and Heavey, Jack and Vullikanti, Anil and Prakash, B Aditya},
booktitle={Proceedings of the 2024 SIAM International Conference on Data Mining (SDM)},
pages={280--288},
year={2024},
organization={SIAM}
}
```