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Quantitative mapping of scientific research—The case of electrical conducting polymer nanocomposite
Authors:Pei-Chun LeeAuthor Vitae  Hsin-Ning SuAuthor Vitae
Institution:
  • a SPRU, Science and Technology Policy Research, The Freeman Centre, University of Sussex, Brighton, BN1 9QE, UK
  • b Graduate Institute of Technology and Innovation Management, National Chengchi University, No. 64, Sec. 2, Chih-nan Rd. Wenshan, Taipei, 116, Taiwan
  • c Science and Technology Policy Research and Information Center, National Applied Research laboratories, 14 F., No. 106, Sec. 2, He-Ping E. Rd., Taipei, 106, Taiwan
  • Abstract:This study aims to understand knowledge structure both quantitatively and visually by integrating keyword analysis and social network analysis of scientific papers. The methodology proposed in this study is capable of creating a three-dimensional “Research focus parallelship network” and a “Keyword Co-occurrence Network”, together with a two-dimensional knowledge map. The network and knowledge map can be depicted differently by choosing different information for the network actor, i.e. country, institute, paper and keyword, to reflect knowledge structures from macro, to meso, to micro-levels. A total of 223 highly cited papers published by 142 institutes and 26 countries are analyzed in this study. China and the US are the two countries located at the core of knowledge structure and China is ranked no. 1. This quantitative exploration provides a way to unveil important or emerging components in scientific development and also to visualize knowledge; thus an objective evaluation of scientific research is possible for quantitative technology management.
    Keywords:Keyword  Network theory  Knowledge structure  Electrical conduction  Polymer nanocomposite
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