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Mapping research spotlights for different regions in China

Author

Listed:
  • Zhigang Hu

    (Dalian University of Technology
    Dalian University of Technology)

  • Fangqi Guo

    (Dalian University of Technology
    Dalian University of Technology)

  • Haiyan Hou

    (Dalian University of Technology
    Dalian University of Technology)

Abstract

To reveal China’s regional disparity both in research output and preferential research areas is the main purpose of this study. For this study, we investigated the research outputs of all 31 regions (27 provinces and 4 municipalities) in mainland China. The investigated dataset was sourced from CNKI, one of China’s largest domestic academic databases. To measure research preferences between regions, we used the function of cosine distance rather than Euclidean distance. Clustering method was employed to classify the regions according to their similarity/disparity. In the end, six clusters were generated. Each cluster is different in research preferences. For example, Inner Mongolia in Cluster D is featured with the emphasis on animal handcraft; while Hubei province in Cluster A is characterized by a wide range of research areas.

Suggested Citation

  • Zhigang Hu & Fangqi Guo & Haiyan Hou, 2017. "Mapping research spotlights for different regions in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 779-790, February.
    • Handle: RePEc:spr:scient:v:110:y:2017:i:2:d:10.1007_s11192-016-2175-z
    DOI: 10.1007/s11192-016-2175-z
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    References listed on IDEAS

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    Cited by:

    1. van der Wouden, Frank, 2022. "Are Chinese cities getting smarter in terms of knowledge and technology they produce?," World Development, Elsevier, vol. 150(C).
    2. Csomós, György, 2018. "Reprint of “A spatial scientometric analysis of the publication output of cities worldwide”," Journal of Informetrics, Elsevier, vol. 12(2), pages 547-566.
    3. Lutz Bornmann & Rüdiger Mutz & Robin Haunschild & Felix Moya-Anegon & Mirko Almeida Madeira Clemente & Moritz Stefaner, 2021. "Mapping the impact of papers on various status groups in excellencemapping.net: a new release of the excellence mapping tool based on citation and reader scores," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(11), pages 9305-9331, November.
    4. Barbara S. Lancho-Barrantes & Francisco J. Cantu-Ortiz, 2021. "Quantifying the publication preferences of leading research universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2269-2310, March.
    5. Cui Zhang & Jing Guo, 2017. "China’s international research collaboration: evidence from a panel gravity model," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 1129-1139, November.

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