Introducing Reproducibility to Citation Analysis: a Case Study in the Earth Sciences
公开 Deposited- Abstract
Objectives:
- Replicate methods from a 2019 study of Earth Science researcher citation practices.
- Calculate programmatically whether researchers in Earth Science rely on a smaller subset of literature than estimated by the 80/20 rule.
- Determine whether these reproducible citation analysis methods can be used to analyze open access uptake.
Methods: Replicated methods of a prior citation study provide an updated transparent, reproducible citation analysis protocol that can be replicated with Jupyter Notebooks.
Results: This study replicated the prior citation study’s conclusions, and also adapted the author’s methods to analyze the citation practices of Earth Scientists at four institutions. We found that 80% of the citations could be accounted for by only 7.88% of journals, a key metric to help identify a core collection of titles in this discipline. We then demonstrated programmatically that 36% of these cited references were available as open access.
Conclusions: Jupyter Notebooks are a viable platform for disseminating replicable processes for citation analysis. A completely open methodology is emerging and we consider this a step forward. Adherence to the 80/20 rule aligned with institutional research output, but citation preferences are evident. Reproducible citation analysis methods may be used to analyze open access uptake, however, results are inconclusive. It is difficult to determine whether an article was open access at the time of citation, or became open access after an embargo.
- Creator
- Date Issued
- 2021
- Additional Information
- The authors contributed to this project in the following roles: ST: Conceptualization, Data Curation, Methodology, Writing, Validation, Visualization, Project Management. WT: Conceptualization, Investigation, Validation, Writing. MW: Conceptualization, Writing, Validation. PW: Conceptualization, Methodology, Software, Visualization, Data Curation, Writing.
- Academic Affiliation
- Journal Title
- Journal Issue/Number
- 2
- Journal Volume
- 10
- 最新修改
- 2022-05-09
- Resource Type
- 权利声明
- License
- DOI
- ISSN
- 2161-3974
- Language
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Introducing_Reproducibility_to_Citation_Analysis.pdf | 2022-05-09 | 公开 | 下载 |