How do software citation formats evolve over time? A longitudinal analysis of R programming language packages

• URL: http://arxiv.org/abs/2307.09390v1
• Date: Mon, 17 Jul 2023 09:18:57 GMT
• Title: How do software citation formats evolve over time? A longitudinal analysis of R programming language packages
• Authors: Yuzhuo Wang, Kai Li
• Abstract summary: This study compares and analyzes a longitudinal dataset of citation formats of all R packages collected in 2021 and 2022. We investigate the different document types underlying the citations and what metadata elements in the citation formats changed over time.
• Score: 12.082972614614413
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Under the data-driven research paradigm, research software has come to play crucial roles in nearly every stage of scientific inquiry. Scholars are advocating for the formal citation of software in academic publications, treating it on par with traditional research outputs. However, software is hardly consistently cited: one software entity can be cited as different objects, and the citations can change over time. These issues, however, are largely overlooked in existing empirical research on software citation. To fill the above gaps, the present study compares and analyzes a longitudinal dataset of citation formats of all R packages collected in 2021 and 2022, in order to understand the citation formats of R-language packages, important members in the open-source software family, and how the citations evolve over time. In particular, we investigate the different document types underlying the citations and what metadata elements in the citation formats changed over time. Furthermore, we offer an in-depth analysis of the disciplinarity of journal articles cited as software (software papers). By undertaking this research, we aim to contribute to a better understanding of the complexities associated with software citation, shedding light on future software citation policies and infrastructure.

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