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Overview

This repository contains code, data, and figures associated with a forthcoming preprint describing a decade of CDC-authored publications using topic modeling and bibliometrics.

Preprint link: https://www.medrxiv.org/content/10.1101/2025.03.07.25323572v1

The source of publications analyzed in this project is CDC Science Clips, a public-facing database of publications by CDC authors. This data can be accessed here: https://www.cdc.gov/library/sciclips/download/.

Please note that we accessed Science Clips for this project on 5/3/24, so if you want to use our code with a new copy of Science Clips, your results may differ from ours. We are happy to provide the version of Science Clips used in our analyses on request, but do not include it in this repository due to file size restrictions in GitHub.

Acknowlegements

We used https://github.com/allenai/specter and https://github.com/MaartenGr/BERTopic in our topic model and analyses.

Code

This folder contains code to regenerate analyses associated with the preprint.

To regenerate the analyses, please run "create_CDC_table.ipynb" first in order to generate a table necessary for the other notebooks to run.

Data

This folder contains data used in this preprint.

Altmetric Duplicates Removed: This folder is provided to show a record of deduplication of certain Altmetric records. Most of these duplicates appear to occur when there is a PMID/DOI mismatch or multiple versions of the same publication. These were removed in order to ensure no duplicate publications were included in the dataset.

Data Pulls: This folder contains the raw data pulls from Altmetric Explorer (explorer.altmetric.com) and BMJ Impact Analytics for the publications in our dataset. A Word document readme describes deduplication prior to the creation of the CDC data table used to create analyses and figures (in "Code/create_CDC_table.ipynb").

In the main folder, you will find the following files:

• "Altmetric_accessed20240702_ScienceClips_accessed20240503_2014to2023.xlsx": Altmetric data associated with Science Clips publications. Science Clips was accessed 5/3/2024 and this dataset covers publications from 2014-2023. Altmetric data was accessed via Altmetric Explorer on 7/2/2024.
• "BMJ_accessed20240702_ScienceClips_accessed20240503_2014to2023.xlsx": BMJ Impact Analytics data associated with Science Clips publications. Science Clips was accessed 5/3/2024 and this dataset covers publications from 2014-2023. BMJ Impact Analytics data was accessed via Altmetric Explorer on 7/2/2024.
• Embeddings_Visualizations_BestOverall_reduced.xlsx": UMAP 2D embeddings of publications in our dataset that are used to generate a topic map of publications (see "visualize_clusters.ipynb"). Some columns are removed from the original version of this data due to file size restrictions in GitHub. We are happy to provide the full version upon request.
• "Reviews_FinalLabels.xlsx": This file shows the review process for generating labels for each of the clusters in our topic model. It is used to help create tables and figures for our analysis.
• ScienceClips_with_Topics_bestoverall_nneigh25_2014-2023_forImpact_reduced.xlsx" This file contains the results of our topic model. For more information about how we generated these results, please consult the "Topic Modeling" folder. Some columns are removed from the original version of this data due to file size restrictions in GitHub. We are happy to provide the full version upon request.

Results

This folder contains figures and tables generated by notebooks in the "Code" folder. Final versions of figures are also included as a .zip file.

Topic Modeling

This folder contains results from topic modeling of our publications dataset:

• "FinalModel_SPECTER_20240828": This folder contains files that save a lighter version of the full model used in the publication that can be used to classify new publications into our 46 topic themes.
• "2024_CDC_Topic_Model_Code_Workbook": An HTML and an .ipynb version of this notebook are included. The HTML version shows the outputs from our original analyses. The .ipynb version can be used to test our methods for generating a topic modeling pipeline for scientific publications.
• "README_Reproducibility_2024_CDC_Topic_Model_Code_Workbook": This notebook demonstrates potential reproducibility issues if you test our methods for generating our topic model.
• "Topic_Modeling_Library_Versions.txt": This text file lists the versions of libraries used in our Jupyter lab environment when we generated our topic model.

Public Domain Standard Notice

This repository constitutes a work of the United States Government and is not subject to domestic copyright protection under 17 USC § 105. This repository is in the public domain within the United States, and copyright and related rights in the work worldwide are waived through the CC0 1.0 Universal public domain dedication. All contributions to this repository will be released under the CC0 dedication. By submitting a pull request you are agreeing to comply with this waiver of copyright interest.

License Standard Notice

The repository utilizes code licensed under the terms of the Apache Software License and therefore is licensed under ASL v2 or later.

This source code in this repository is free: you can redistribute it and/or modify it under the terms of the Apache Software License version 2, or (at your option) any later version.

This source code in this repository is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the Apache Software License for more details.

You should have received a copy of the Apache Software License along with this program. If not, see http://www.apache.org/licenses/LICENSE-2.0.html

The source code forked from other open source projects will inherit its license.

Privacy Standard Notice

This repository contains only non-sensitive, publicly available data and information. All material and community participation is covered by the Disclaimer and Code of Conduct. For more information about CDC's privacy policy, please visit http://www.cdc.gov/other/privacy.html.

Contributing Standard Notice

Anyone is encouraged to contribute to the repository by forking and submitting a pull request. (If you are new to GitHub, you might start with a basic tutorial.) By contributing to this project, you grant a world-wide, royalty-free, perpetual, irrevocable, non-exclusive, transferable license to all users under the terms of the Apache Software License v2 or later.

All comments, messages, pull requests, and other submissions received through CDC including this GitHub page may be subject to applicable federal law, including but not limited to the Federal Records Act, and may be archived. Learn more at http://www.cdc.gov/other/privacy.html.

Records Management Standard Notice

This repository is not a source of government records, but is a copy to increase collaboration and collaborative potential. All government records will be published through the CDC web site.

Additional Standard Notices

Please refer to CDC's Template Repository for more information about contributing to this repository, public domain notices and disclaimers, and code of conduct.