可视化
计算机科学
数据科学
科学网
研究政策
宏
科学政策
信息可视化
图书馆学
数据挖掘
政治学
梅德林
公共行政
法学
程序设计语言
摘要
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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