This repository contains the code to import and integrate the book and rating data that we work with. It imports and integrates data from several sources in a homogenous tabular outputs; import scripts are primarily Rust, with Python implement analyses.

If you use these scripts in any published research, cite our paper (PDF):

Michael D. Ekstrand and Daniel Kluver. 2021. Exploring Author Gender in Book Rating and Recommendation. User Modeling and User-Adapted Interaction (February 2021) DOI:10.1007/s11257-020-09284-2.

We also ask that you contact Michael Ekstrand to let us know about your use of the data, so we can include your paper in our list of relying publications.

Note: the limitations section of the paper contains important information about the limitations of the data these scripts compile. Do not use the gender information in this data data or tools without understanding those limitations. In particular, VIAF's gender information is incomplete and, in a number of cases, incorrect.

In addition, several of the data sets integrated by this project come from other sources with their own publications. If you use any of the rating or interaction data, cite the appropriate original source paper. For each data set below, we have provided a link to the page that describes the data and its appropriate citation.

See the documentation site for details on using and extending these tools.

This project uses submodules — clone with git clone --recursive.

Running Everything

The dependencies are managed with Pixi and declared in pixi.toml. To install the environment, run:

$ pixi install

The dev environment provides additional useful software for making modifications to the code, such as the Python linter.

You can run the entire import process with:

$ pixi run repro-all

[!NOTE]

If you are going to develop on the tools, set up pre-commit with:

$ pixi run -e dev pre-commit install

Copyright and Acknowledgements

Copyright ⓒ 2023–2024 Drexel University, 2020–2023 Boise State University. Distributed under the MIT License; see LICENSE.md. This material is based upon work supported by the National Science Foundation under Grant No. IIS 17-51278. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.