A review on the novelty measurements of academic papers
Yi Zhao and
Chengzhi Zhang ()
Additional contact information
Yi Zhao: Nanjing University of Science and Technology
Chengzhi Zhang: Nanjing University of Science and Technology
Scientometrics, 2025, vol. 130, issue 2, No 9, 727-753
Abstract:
Abstract Novelty evaluation is vital for the promotion and management of innovation. With the advancement of information techniques and the open data movement, some progress has been made in novelty measurements. Tracking and reviewing novelty measures provides a data-driven way to assess contributions, progress, and emerging directions in the science field. As academic papers serve as the primary medium for the dissemination, validation, and discussion of scientific knowledge, this review aims to offer a systematic analysis of novelty measurements for scientific papers. We began by comparing the differences between scientific novelty and four similar concepts, including originality, scientific innovation, creativity, and scientific breakthrough. Next, we reviewed the types of scientific novelty. Then, we classified existing novelty measures according to data types and reviewed the measures for each type. Subsequently, we surveyed the approaches employed in validating novelty measures and examined the current tools and datasets associated with these measures. Finally, we proposed several open issues for future studies.
Keywords: Scientific novelty; Dimensions of novelty; Novelty measures (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s11192-025-05234-0 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:130:y:2025:i:2:d:10.1007_s11192-025-05234-0
Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192
DOI: 10.1007/s11192-025-05234-0
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 ().