IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v12y2025i1d10.1057_s41599-025-04617-1.html
   My bibliography  Save this article

Evolution and impact of the science of science: from theoretical analysis to digital-AI driven research

Author

Listed:
  • Jianhua Hou

    (Panyu District)

  • Bili Zheng

    (Panyu District)

  • Hao Li

    (Panyu District)

  • Wenjing Li

    (Panyu District)

Abstract

The Science of Science (SoS) examines the mechanisms driving the development and societal role of science, evolving from its sociological roots into a data-driven discipline. This paper traces the progression of SoS from its early focus on the social functions of science to the current era, characterized by large-scale quantitative analysis and AI-driven methodologies. Scientometrics, a key branch of SoS, has utilized statistical methods and citation analysis to understand scientific growth and knowledge diffusion. With the rise of big data and complex network theory, SoS has transitioned toward more refined analyses, leveraging artificial intelligence (AI) for predictive modeling, sentiment annotation, and entity extraction. This paper explores the application of AI in SoS, highlighting its role as a surrogate, quant, and arbiter in advancing data processing, data analysis and peer review. The integration of AI has ushered in a new paradigm for SoS, enhancing its predictive accuracy and providing deeper insights into the internal dynamics of science and its impact on society.

Suggested Citation

  • Jianhua Hou & Bili Zheng & Hao Li & Wenjing Li, 2025. "Evolution and impact of the science of science: from theoretical analysis to digital-AI driven research," Palgrave Communications, Palgrave Macmillan, vol. 12(1), pages 1-9, December.
  • Handle: RePEc:pal:palcom:v:12:y:2025:i:1:d:10.1057_s41599-025-04617-1
    DOI: 10.1057/s41599-025-04617-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-025-04617-1
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/s41599-025-04617-1?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.

    More about this item

    Statistics

    Access and download statistics

    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:pal:palcom:v:12:y:2025:i:1:d:10.1057_s41599-025-04617-1. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.com/ .

    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.