Visualization of global science and technology policy research structure

Abstract

Abstract This study proposes an approach for visualizing knowledge structures that creates a “research‐focused parallelship network,” “keyword co‐occurrence network,” and a knowledge map to visualize Sci‐Tech policy research structure. A total of 1,125 Sci‐Tech policy‐related papers (873 journal papers [78%], 205 conference papers [18%], and 47 review papers [4%]) have been retrieved from the Web of Science database for quantitative analysis and mapping. Different network and contour maps based on these 1,125 papers can be constructed by choosing different information as the main actor, such as the paper title, the institute, the country, or the author keywords, to reflect Sci‐Tech policy research structures in micro‐, meso‐, and macro‐levels, respectively. The quantitative way of exploring Sci‐Tech policy research papers is investigated to unveil important or emerging Sci‐Tech policy implications as well as to demonstrate the dynamics and visualization of the evolution of Sci‐Tech policy research.

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No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 7 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.