IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v17y2023i4s175115772300072x.html
   My bibliography  Save this article

High acknowledgement index: Characterizing research supporters with factors of acknowledgement affecting paper citation counts

Author

Listed:
  • Heo, Go Eun
  • Ko, Young Soo
  • Xie, Qing
  • Song, Min

Abstract

The acknowledgments section of scientific papers is paramount in academic production, providing valuable insights into the individuals and organizations involved in the research process. Developing a standard index of acknowledgments would provide a significant metric for measuring institutional and researcher influence. However, the absence of standardized formats has impeded effective analysis of information in acknowledgement sections. This study develop an acknowledgement index utilizing automated text-mining techniques to address these limitations. In addition, we propose two methods to disambiguate research supporters in the acknowledgement section: entity scores based on specific keywords and research similarity scores calculated through co-references. Based on our investigation, we explore the characteristics of research supporters with high acknowledgement index scores and examine the correlation between each acknowledgement index and their performance. Notably, paper citation strongly correlates with research supporters' performance. Next, our analysis delves into the impact of acknowledgement and entity types on paper citations. Our findings reveal that acknowledgments with only person names exert the most significant impact on paper citation.

Suggested Citation

  • Heo, Go Eun & Ko, Young Soo & Xie, Qing & Song, Min, 2023. "High acknowledgement index: Characterizing research supporters with factors of acknowledgement affecting paper citation counts," Journal of Informetrics, Elsevier, vol. 17(4).
    • Handle: RePEc:eee:infome:v:17:y:2023:i:4:s175115772300072x
    DOI: 10.1016/j.joi.2023.101447
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S175115772300072X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.joi.2023.101447?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Adèle Paul-Hus & Nadine Desrochers & Rodrigo Costas, 2016. "Characterization, description, and considerations for the use of funding acknowledgement data in Web of Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(1), pages 167-182, July.
    2. Adèle Paul-Hus & Adrián A Díaz-Faes & Maxime Sainte-Marie & Nadine Desrochers & Rodrigo Costas & Vincent Larivière, 2017. "Beyond funding: Acknowledgement patterns in biomedical, natural and social sciences," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-14, October.
    3. Nadine Desrochers & Adèle Paul‐Hus & Jen Pecoskie, 2017. "Five decades of gratitude: A meta‐synthesis of acknowledgments research," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(12), pages 2821-2833, December.
    4. Min Song & Keun Young Kang & Tatsawan Timakum & Xinyuan Zhang, 2020. "Examining influential factors for acknowledgements classification using supervised learning," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-21, February.
    5. Li Tang & John P. Walsh, 2010. "Bibliometric fingerprints: name disambiguation based on approximate structure equivalence of cognitive maps," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(3), pages 763-784, September.
    6. Katherine W. McCain, 2018. "Beyond Garfield’s Citation Index: an assessment of some issues in building a personal name Acknowledgments Index," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 605-631, February.
    7. Xie, Qing & Wang, Jiamin & Kim, Giyeong & Lee, Soobin & Song, Min, 2021. "A sensitivity analysis of factors influential to the popularity of shared data in data repositories," Journal of Informetrics, Elsevier, vol. 15(3).
    8. Adèle Paul-Hus & Nadine Desrochers, 2019. "Acknowledgements are not just thank you notes: A qualitative analysis of acknowledgements content in scientific articles and reviews published in 2015," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-13, December.
    9. Adrián A. Díaz-Faes & María Bordons, 2014. "Acknowledgments in scientific publications: Presence in Spanish science and text patterns across disciplines," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(9), pages 1834-1849, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alberto Baccini & Eugenio Petrovich, 2022. "Normative versus strategic accounts of acknowledgment data: The case of the top-five journals of economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 603-635, January.
    2. Nina Smirnova & Philipp Mayr, 2023. "A comprehensive analysis of acknowledgement texts in Web of Science: a case study on four scientific domains," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 709-734, January.
    3. Wen Lou & Jiangen He & Lingxin Zhang & Zhijie Zhu & Yongjun Zhu, 2023. "Support behind the scenes: the relationship between acknowledgement, coauthor, and citation in Nobel articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5767-5790, October.
    4. Pengfei Jia & Weixi Xie & Guangyao Zhang & Xianwen Wang, 2023. "Do reviewers get their deserved acknowledgments from the authors of manuscripts?," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5687-5703, October.
    5. Gianluca Fabiano & Andrea Marcellusi & Giampiero Favato, 2020. "Public–private contribution to biopharmaceutical discoveries: a bibliometric analysis of biomedical research in UK," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 153-168, July.
    6. Shanwu Tian & Xiurui Xu & Ping Li, 2021. "Acknowledgement network and citation count: the moderating role of collaboration network," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7837-7857, September.
    7. Belén Álvarez-Bornstein & Fernanda Morillo & María Bordons, 2017. "Funding acknowledgments in the Web of Science: completeness and accuracy of collected data," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1793-1812, September.
    8. Weishu Liu & Li Tang & Guangyuan Hu, 2020. "Funding information in Web of Science: an updated overview," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1509-1524, March.
    9. Maia Chankseliani, 2023. "Who funds the production of globally visible research in the Global South?," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 783-801, January.
    10. Liu, Weishu, 2021. "Caveats for the use of Web of Science Core Collection in old literature retrieval and historical bibliometric analysis," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    11. Adèle Paul-Hus & Nadine Desrochers, 2019. "Acknowledgements are not just thank you notes: A qualitative analysis of acknowledgements content in scientific articles and reviews published in 2015," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-13, December.
    12. Nadine Desrochers & Adèle Paul‐Hus & Jen Pecoskie, 2017. "Five decades of gratitude: A meta‐synthesis of acknowledgments research," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(12), pages 2821-2833, December.
    13. Corsini, Alberto & Pezzoni, Michele, 2023. "Does grant funding foster research impact? Evidence from France," Journal of Informetrics, Elsevier, vol. 17(4).
    14. Keith Head & Yao Amber Li & Asier Minondo, 2019. "Geography, Ties, and Knowledge Flows: Evidence from Citations in Mathematics," The Review of Economics and Statistics, MIT Press, vol. 101(4), pages 713-727, October.
    15. Deyun Yin & Kazuyuki Motohashi & Jianwei Dang, 2020. "Large-scale name disambiguation of Chinese patent inventors (1985–2016)," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 765-790, February.
    16. Li Tang & Jennifer Kuzma & Xi Zhang & Xinyu Song & Yin Li & Hongxu Liu & Guangyuan Hu, 2023. "Synthetic biology and governance research in China: a 40-year evolution," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 5293-5310, September.
    17. Li Tang & Philip Shapira, 2011. "Regional development and interregional collaboration in the growth of nanotechnology research in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(2), pages 299-315, February.
    18. Alison M. J. Buchan & Eva Jurczyk & Ruth Isserlin & Gary D. Bader, 2016. "Global neuroscience and mental health research: a bibliometrics case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(1), pages 515-531, October.
    19. Li, Heyang & Wu, Meijun & Wang, Yougui & Zeng, An, 2022. "Bibliographic coupling networks reveal the advantage of diversification in scientific projects," Journal of Informetrics, Elsevier, vol. 16(3).
    20. Liu, Meijun & Hu, Xiao, 2021. "Will collaborators make scientists move? A Generalized Propensity Score analysis," Journal of Informetrics, Elsevier, vol. 15(1).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:infome:v:17:y:2023:i:4:s175115772300072x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/joi .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.