The use of ChatGPT for identifying disruptive papers in science: a first exploration

Lutz Bornmann (), Lingfei Wu () and Christoph Ettl ()
Additional contact information
Lutz Bornmann: Administrative Headquarters of the Max Planck Society
Lingfei Wu: University of Pittsburgh
Christoph Ettl: Administrative Headquarters of the Max Planck Society

Scientometrics, 2024, vol. 129, issue 11, No 28, 7165 pages

Abstract: Abstract ChatGPT has arrived in quantitative research evaluation. With the exploration in this Letter to the Editor, we would like to widen the spectrum of the possible use of ChatGPT in bibliometrics by applying it to identify disruptive papers. The identification of disruptive papers using publication and citation counts has become a popular topic in scientometrics. The disadvantage of the quantitative approach is its complexity in the computation. The use of ChatGPT might be an easy to use alternative.

Keywords: Bibliometrics; ChatGPT; Disruption (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11192-024-05176-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:129:y:2024:i:11:d:10.1007_s11192-024-05176-z

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192

DOI: 10.1007/s11192-024-05176-z

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().