Holding out the promise of Lasswell's dream: Big data analytics in public policy research and teaching
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10441611" target="_blank" >RIV/00216208:11320/21:10441611 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=4YlSZ~wner" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=4YlSZ~wner</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1111/ropr.12448" target="_blank" >10.1111/ropr.12448</a>
Alternative languages
Result language
angličtina
Original language name
Holding out the promise of Lasswell's dream: Big data analytics in public policy research and teaching
Original language description
While the emergence of big data raises concerns regarding governance and public policy, it also creates opportunities for diversifying the toolkit for analysis for the policy sciences as a whole, i.e., research concerning policy analysis as well as policy studies. Further, it opens avenues for practice, which together with research requires adaptation in teaching curricula if policy education were to remain relevant. However, it is not clear to what extent this opportunity is being realized in public policy research and teaching. In this study, we examine the prevalence of big data analytics in public policy research and pedagogy using bibliometric analysis and topic modeling for the former, and content analysis of course titles and descriptions for the latter. We find that despite significant scope for application of various big data techniques, the use of these analytic techniques in public policy has been largely limited to select institutions in a few countries. Further, data science has received limited attention in policy pedagogy, once again with significant geographic variation in its prevalence. We conclude that, to stay relevant, the policy sciences need to pay more attention to the integration of big data techniques in policy research, pedagogy, and thereby practice.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Review of Policy Research
ISSN
1541-132X
e-ISSN
1541-1338
Volume of the periodical
38
Issue of the periodical within the volume
6
Country of publishing house
US - UNITED STATES
Number of pages
21
Pages from-to
640-660
UT code for WoS article
000694642700001
EID of the result in the Scopus database
2-s2.0-85114510375