hyperbard / README.md
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Dataset Card for Hyperbard (Dataset)

Table of Contents

Dataset Description

Dataset Summary

First release of Hyperbard.

Hyperbard is a dataset of diverse relational data representations derived from Shakespeare's plays. Our representations range from simple graphs capturing character co-occurrence in single scenes to hypergraphs encoding complex communication settings and character contributions as hyperedges with edge-specific node weights. By making multiple intuitive representations readily available for experimentation, we facilitate rigorous representation robustness checks in graph learning, graph mining, and network analysis, highlighting the advantages and drawbacks of specific representations. 

The code used to create Hyperbard is maintained on GitHub

Supported Tasks and Leaderboards

[More Information Needed]

Languages

The class labels in the dataset are in English

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

[More Information Needed]

Data Splits

[More Information Needed]

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

This dataset was shared by Corinna Coupette, Jilles Vreeken, Bastian Rieck

Licensing Information

The license for this dataset is http://creativecommons.org/licenses/by-nc/2.0/

Citation Information

@dataset{corinna_coupette_2022_6627159,
  author       = {Corinna Coupette and
                  Jilles Vreeken and
                  Bastian Rieck},
  title        = {Hyperbard (Dataset)},
  month        = jun,
  year         = 2022,
  publisher    = {Zenodo},
  version      = {0.0.1},
  doi          = {10.5281/zenodo.6627159},
  url          = {https://doi.org/10.5281/zenodo.6627159}
}

Contributions

[More Information Needed]