The use of ChatGPT for identifying disruptive papers in science: a first exploration
Lutz Bornmann, Lingfei Wu, C. Ettl
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.
Topics & Concepts
Data scienceComputer scienceSociologyArtificial Intelligence in Healthcare and EducationMisinformation and Its ImpactsExplainable Artificial Intelligence (XAI)