Science Score: 31.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
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○.zenodo.json file
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○DOI references
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○Academic publication links
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (7.1%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: HGX-Team
- Default Branch: main
- Size: 314 KB
Statistics
- Stars: 3
- Watchers: 1
- Forks: 1
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
HGX data
Collection of datasets associated with the library Hypergraphx for higher-order network analysis in Python.
Sources
We collected several hypergraph datasets from different sources. The source of the data is acknowledged on the respective presentation page and we provide the BibTeX for a correct reference in your articles (please write us or provide a correction when needed).
Most of the time, source data is naturally a hypergraph. However, sometimes hypergraphs need to be inferred from data stored as a collection of pairwise interactions. This operation is debatable and not trivial, therefore in this cases we also provide original pairwise data.
Face-to-face interactions data
High school
Contacts and friendship relations between students in a high school in Marseilles, France, in December 2013. * TL;DR: [Human face-to-face interactions][Temporal][Labelled nodes] * Details & Download
Primary school
Contacts between the children and teachers in a primary school * TL;DR: [Human face-to-face interactions][Temporal][Labelled nodes] * Details & Download
Hospital
Contacts between patients and healthcare workers in a hospital ward in Lyon, France, from Monday, December 6, 2010 at 1:00 pm to Friday, December 10, 2010 at 2:00 pm. * TL;DR: [Human face-to-face interactions][Temporal][Labelled nodes] * Details & Download
Workplace
Contacts between individuals measured in an office building in France, from June 24 to July 3, 2013. * TL;DR: [Human face-to-face interactions][Temporal][Labelled nodes] * Details & Download
Conference (Hypertext)
Face-to-face interactions during ACM Hypertext 2009 conference in Torino, Italy (June 29 - July 1, 2009). * TL;DR: [Human face-to-face interactions][Temporal] * Details & Download
Conference (SFHH)
Face-to-face interactions during SFHH conference in Nice, France (June 4-5, 2009). * TL;DR: [Human face-to-face interactions][Temporal] * Details & Download
E-mails
Enron
Dataset is provided by Chodrow and Mellor (2020). * TL;DR: [E-mails][Directed] * Details & Download
EU
Dataset is from SNAP (Leskovec and Krevl 2014). * TL;DR: [E-mails][Directed] * Details & Download
Citations
Dm
Subsets of a DBLP citation dataset (Sinha et al. 2015). The subsets consist of papers published in the venues of data mining. * TL;DR: [Data mining papers][Directed] * Details & Download
Software
Subsets of a DBLP citation dataset (Sinha et al. 2015). The subsets consist of papers published in the venues of software engineering. * TL;DR: [Software papers][Directed] * Details & Download
Bitcoin
2014
The original dataset are provided by Wu et al. (2021), and it contains frst 1,500,000 transactions in 11/2014. * TL;DR: [Bitcoin transactions][Directed] * Details & Download
2015
The original dataset are provided by Wu et al. (2021), and it contains frst 1,500,000 transactions in 06/2015. * TL;DR: [Bitcoin transactions][Directed] * Details & Download
2016
The original dataset are provided by Wu et al. (2021), and it contains frst 1,500,000 transactions in 01/2016. * TL;DR: [Bitcoin transactions][Directed] * Details & Download
Question & Answer
Math
Log data of a question answering site, stack exchange, provided at Archive (2022). We choose math-overfow, which covers mathematical questions. * TL;DR: [Q&A][Directed] * Details & Download
Server
Log data of a question answering site, stack exchange, provided at Archive (2022). We choose server-fault, which treats server related issues. * TL;DR: [Q&A][Directed] * Details & Download
Metabolic
iaf1260b
Dataset iAF1260b provided by Yadati et al. (2020). * TL;DR: [Metabolic][Directed] * Details & Download
iJO1366
Dataset iJO1366 provided by Yadati et al. (2020). * TL;DR: [Metabolic][Directed] * Details & Download
Owner
- Name: HGX-Team
- Login: HGX-Team
- Kind: organization
- Repositories: 1
- Profile: https://github.com/HGX-Team
Citation (citations/dm/README.md)
# Citation_dm
We use two citation hypergraphs, citation-data mining and citation-software,
which we create from pairwise citation networks, as suggested by Yadati et al. Nodes are the authors of publications. Assume that a paper A, which is coauthored by {v1, v2, v3}, cited another paper B, which is co-authored by {v4, v5}.
Then, this citation leads to a hyperarc where the head set is {v4, v5} and the tail set is
{v1, v2, v3}. As pairwise citation networks, we use subsets of a DBLP citation dataset
(Sinha et al. 2015). The subsets consist of papers published in the venues of data mining and software engineering, respectively.
In addition, we flter out all papers
co-authored by more than 10 authors to minimize the impact of such outliers.
* [Download]()
When this data is used in published research or for visualization purposes, please cite the following papers:
```
@article{kim2023reciprocity,
title={Reciprocity in directed hypergraphs: measures, findings, and generators},
author={Kim, Sunwoo and Choe, Minyoung and Yoo, Jaemin and Shin, Kijung},
journal={Data Mining and Knowledge Discovery},
volume={37},
number={6},
pages={2330--2388},
year={2023},
publisher={Springer}
}
@inproceedings{yadati2021graph,
title={Graph neural networks for soft semi-supervised learning on hypergraphs},
author={Yadati, Naganand and Gao, Tingran and Asoodeh, Shahab and Talukdar, Partha and Louis, Anand},
booktitle={Pacific-Asia Conference on Knowledge Discovery and Data Mining},
pages={447--458},
year={2021},
organization={Springer}
}
@inproceedings{sinha2015overview,
title={An overview of microsoft academic service (mas) and applications},
author={Sinha, Arnab and Shen, Zhihong and Song, Yang and Ma, Hao and Eide, Darrin and Hsu, Bo-June and Wang, Kuansan},
booktitle={Proceedings of the 24th international conference on world wide web},
pages={243--246},
year={2015}
}
```
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