Parallel or intersecting lines? Intelligent bibliometrics for investigating the involvement of data science in policy analysis
Zhang, Yi and Porter, Alan L. and Cunningham, Scott W. and Chiavetta, Denise and Newman, Nils (2021) Parallel or intersecting lines? Intelligent bibliometrics for investigating the involvement of data science in policy analysis. IEEE Transactions on Engineering Management, 68 (5). pp. 1259-1271. ISSN 0018-9391 (https://doi.org/10.1109/TEM.2020.2974761)
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Abstract
Efforts to involve data science in policy analysis can be traced back decades but transforming analytic findings into decisions is still far from straightforward task. Data-driven decision-making requires understanding approaches, practices, and research results from many disciplines, which makes it interesting to investigate whether data science and policy analysis are moving in parallel or whether their pathways have intersected. Our investigation, from a bibliometric perspective, is driven by a comprehensive set of research questions, and we have designed an intelligent bibliometric framework that includes a series of traditional bibliometric approaches and a novel method of charting the evolutionary pathways of scientific innovation, which is used to identify predecessor–descendant relationships in technological topics. Our investigation reveals that data science and policy analysis have intersecting lines, and it can foresee that a cross-disciplinary direction in which policy analysis interacting with data science has become an emergent area in both communities. However, equipped with advanced data analytic techniques, data scientists are moving faster and further than policy analysts. The empirical insights derived from our research should be beneficial to academic researchers and journal editors in related research communities, as well as policy-makers in research institutions and funding agencies.
ORCID iDs
Zhang, Yi, Porter, Alan L., Cunningham, Scott W. ORCID: https://orcid.org/0000-0001-7140-916X, Chiavetta, Denise and Newman, Nils;-
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Item type: Article ID code: 77587 Dates: DateEvent31 October 2021Published9 March 2020Published Online11 February 2020AcceptedNotes: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Subjects: Bibliography. Library Science. Information Resources > Information resources > Electronic information resources
Bibliography. Library Science. Information Resources > Information resources > DatabasesDepartment: Faculty of Humanities and Social Sciences (HaSS) > Government and Public Policy > Politics Depositing user: Pure Administrator Date deposited: 27 Aug 2021 14:47 Last modified: 11 Nov 2024 13:12 URI: https://strathprints.strath.ac.uk/id/eprint/77587