Using data citation to define a knowledge domain: A case study of the Add‐Health dataset

Wei‐Min Fan, Wei Jeng and Muh‐Chyun Tang

Journal of the Association for Information Science & Technology, 2023, vol. 74, issue 1, 81-98

Abstract: To date, most studies in scientometric map and track the main topics in a knowledge domain by measuring publications in core journals or keyword searches in databases. The present study instead proposes a novel metrics in which a knowledge domain is mapped and tracked via articles that cite the same openly accessible dataset. We retrieved 1,537 journal articles citing the National Longitudinal Study of Adolescent to Adult Health (Add‐Health) as the basis for an investigation of the major research topics associated with this dataset and how they evolved over time. To identify the primary research interests associated with the dataset, co‐word network modularity analysis was used. Another novel aspect of this study is that it juxtaposes the research topics identified by the co‐word approach with those generated by topic modeling: an approach that complements network modularity analysis, and allows for cross‐referencing between the results of these two methods. Keyness analysis was also performed to identify significant keywords in different time periods, which enables tracing of research interests in Add‐Health as they evolve. The methodological implications of using data citation as the basis for delineating a knowledge domain and techniques for its mapping are also discussed.

Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/asi.24688

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:bla:jinfst:v:74:y:2023:i:1:p:81-98

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=2330-1635

Access Statistics for this article

More articles in Journal of the Association for Information Science & Technology from Association for Information Science & Technology
Bibliographic data for series maintained by Wiley Content Delivery ().