Holding out the promise of Lasswell's dream: Big data analytics in public policy research and teaching

Ola G. El-Taliawi, Nihit Goyal, Michael Howlett

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

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.

Original languageEnglish
JournalReview of Policy Research
DOIs
Publication statusPublished - 2021

Keywords

  • bibliometric review
  • big data analytics
  • machine learning
  • pedagogy
  • policy sciences
  • public policy
  • topic modeling

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