Mapping knowledge structure by keyword co-occurrence: a first look at journal papers in Technology Foresight

Hsin-Ning Su () and Pei-Chun Lee ()
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Hsin-Ning Su: Science and Technology Policy Research and Information Center, National Applied Research Laboratories
Pei-Chun Lee: Science and Technology Policy Research and Information Center, National Applied Research Laboratories

Scientometrics, 2010, vol. 85, issue 1, No 6, 65-79

Abstract: Abstract This study proposes an approach for visualizing a knowledge structure, the proposed approach creates a three-dimensional “Research focused parallelship network”, a “Keyword Co-occurrence Network”, and a two-dimensional knowledge map to facilitate visualization of the knowledge structure created by journal papers from different perspectives. The networks and knowledge maps can be depicted differently by choosing different information as the network actor, e.g. author, institute or country keyword, to reflect knowledge structures in micro-, meso-, and macro-levels, respectively. Technology Foresight is selected as an example to illustrate the method proposed in this study. A total of 556 author keywords contained in 181 Technology Foresight related papers have been analyzed. European countries, China, India and Brazil are located at the core of Technology Foresight research. Quantitative ways of mapping journal papers are investigated in this study to unveil emerging elements as well as to demonstrate dynamics and visualization of knowledge. The quantitative method provided in this paper shows a possible way of visualizing and evaluating knowledge structure; thus a computerized calculation is possible for potential quantitative applications, e.g. R&D resource allocation, research performance evaluation, science map, etc.

Keywords: Keyword; Network theory; Knowledge structure; Technology Foresight (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (117)

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DOI: 10.1007/s11192-010-0259-8

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