Parallel or Intersecting Lines? Intelligent Bibliometrics for Investigating the Involvement of Data Science in Policy Analysis

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 many disciplines, which makes it interesting investigate whether are moving parallel or their pathways have intersected. Our investigation, a bibliometric perspective, driven by comprehensive set of questions, we designed an intelligent framework that includes series traditional approaches novel method charting the evolutionary scientific innovation, used identify predecessor-descendant relationships technological topics. investigation reveals intersecting lines, foresee cross-disciplinary direction interacting with has become emergent area both communities. However, equipped advanced techniques, scientists faster further than analysts. The empirical insights derived our should beneficial academic researchers journal editors related communities, as well policy-makers institutions funding agencies.