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How is R cited in research outputs? Structure, impacts, and citation standard

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  • Li, Kai
  • Yan, Erjia
  • Feng, Yuanyuan

Abstract

This paper addresses software citation by analyzing how R and its packages are cited in a sample of PLoS papers. A codebook is developed to support a content analysis of the full-text papers. Our results indicate that the software R and its packages are inconsistently cited, as is the case with other scientific software. The inconsistency derives partly from the variety of citation standards currently used for software, and partly from fact that these standards are not well followed by authors on multiple levels. This work sheds light on the future development of software citation standards, especially given the present landscape of conflicting citation practices. Moreover, our approach furnishes a possible blueprint for dealing with the granularity of software entities in scientific citation: we consider citations of the core R software environment, of specific R packages, and of individual functions.

Suggested Citation

  • Li, Kai & Yan, Erjia & Feng, Yuanyuan, 2017. "How is R cited in research outputs? Structure, impacts, and citation standard," Journal of Informetrics, Elsevier, vol. 11(4), pages 989-1002.
    • Handle: RePEc:eee:infome:v:11:y:2017:i:4:p:989-1002
    DOI: 10.1016/j.joi.2017.08.003
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    Citations

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    Cited by:

    1. Lu Jiang & Xinyu Kang & Shan Huang & Bo Yang, 2022. "A refinement strategy for identification of scientific software from bioinformatics publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3293-3316, June.
    2. Alexander Schniedermann, 2021. "A comparison of systematic reviews and guideline-based systematic reviews in medical studies," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(12), pages 9829-9846, December.
    3. Robert Tomaszewski, 2023. "Visibility, impact, and applications of bibliometric software tools through citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(7), pages 4007-4028, July.
    4. Pan, Xuelian & Yan, Erjia & Cui, Ming & Hua, Weina, 2018. "Examining the usage, citation, and diffusion patterns of bibliometric mapping software: A comparative study of three tools," Journal of Informetrics, Elsevier, vol. 12(2), pages 481-493.
    5. Shiwangi Singh & Sanjay Dhir, 2019. "Structured review using TCCM and bibliometric analysis of international cause-related marketing, social marketing, and innovation of the firm," International Review on Public and Nonprofit Marketing, Springer;International Association of Public and Non-Profit Marketing, vol. 16(2), pages 335-347, December.
    6. Li, Kai & Chen, Pei-Ying & Yan, Erjia, 2019. "Challenges of measuring software impact through citations: An examination of the lme4 R package," Journal of Informetrics, Elsevier, vol. 13(1), pages 449-461.
    7. Wang, Yuzhuo & Zhang, Chengzhi, 2020. "Using the full-text content of academic articles to identify and evaluate algorithm entities in the domain of natural language processing," Journal of Informetrics, Elsevier, vol. 14(4).
    8. Enrique Orduña-Malea & Rodrigo Costas, 2021. "Link-based approach to study scientific software usage: the case of VOSviewer," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 8153-8186, September.
    9. Li, Kai & Yan, Erjia, 2018. "Co-mention network of R packages: Scientific impact and clustering structure," Journal of Informetrics, Elsevier, vol. 12(1), pages 87-100.
    10. Pan, Xuelian & Yan, Erjia & Cui, Ming & Hua, Weina, 2019. "How important is software to library and information science research? A content analysis of full-text publications," Journal of Informetrics, Elsevier, vol. 13(1), pages 397-406.
    11. Alsudais, Abdulkareem, 2021. "In-code citation practices in open research software libraries," Journal of Informetrics, Elsevier, vol. 15(2).

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