Journal of the Korean Operations Research and Management Science Society (한국경영과학회지)

The Korean Operations Research and Management Science Society (한국경영과학회)
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A Study on Technology Forecasting based on Co-occurrence Network of Keyword in Multidisciplinary Journals

다학제 분야 학술지의 주제어 동시발생 네트워크를 활용한 기술예측 연구

  • Kim, Hyunuk (Department of Industrial and Management Engineering, POSTECH) ;
  • Ahn, Sang-Jin (Korea Institute of S&T Evaluation and Planning(KISTEP)) ;
  • Jung, Woo-Sung (Department of Industrial and Management Engineering, POSTECH)
  • 김현욱 (포항공과대학교 산업경영공학과) ;
  • 안상진 (한국과학기술기획평가원) ;
  • 정우성 (포항공과대학교 산업경영공학과)
  • Received : 2015.09.30
  • Accepted : 2015.11.18
  • Published : 2015.11.30
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Abstract

Keyword indexed in multidisciplinary journals show trends about science and technology innovation. Nature and Science were selected as multidisciplinary journals for our analysis. In order to reduce the effect of plurality of keyword, stemming algorithm were implemented. After this process, we fitted growth curve of keyword (stem) following bass model, which is a well-known model in diffusion process. Bass model is useful for expressing growth pattern by assuming innovative and imitative activities in innovation spreading. In addition, we construct keyword co-occurrence network and calculate network measures such as centrality indices and local clustering coefficient. Based on network metrics and yearly frequency of keyword, time series analysis was conducted for obtaining statistical causality between these measures. For some cases, local clustering coefficient seems to Granger-cause yearly frequency of keyword. We expect that local clustering coefficient could be a supportive indicator of emerging science and technology.

Keywords

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