Please use this identifier to cite or link to this item:

Title: Mapping Knowledge Structure by Keyword Co-occurrence- A First Look at Journal Papers in Technology Foresight
Authors: 李沛錞
Lee*, Pei-Chun
Su, Hsin-Ning
Contributors: 圖檔所
Keywords: Keyword ;Network theory;Knowledge structure ;Technology Foresight 
Date: 2010-01
Issue Date: 2019-09-19 09:49:21 (UTC+8)
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.
Relation: Scientometrics, Vol.85, No.1, pp.65–79
Data Type: article
DOI 連結:
Appears in Collections:[圖書資訊與檔案學研究所] 期刊論文

Files in This Item:

File Description SizeFormat
134.pdf479KbAdobe PDF186View/Open

All items in 學術集成 are protected by copyright, with all rights reserved.

社群 sharing