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Does the web of science accurately represent chinese scientific performance?

Author

Listed:
  • Fei Shu
  • Charles‐Antoine Julien
  • Vincent Larivière

Abstract

With the significant development of China's economy and scientific activity, its scientific publication activity is experiencing a period of rapid growth. However, measuring China's research output remains a challenge because Chinese scholars may publish their research in either international or national journals, yet no bibliometric database covers both the Chinese and English scientific literature. The purpose of this study is to compare Web of Science (WoS) with a Chinese bibliometric database in terms of authors and their performance, demonstrate the extent of the overlap between the two groups of Chinese most productive authors in both international and Chinese bibliometric databases, and determine how different disciplines may affect this overlap. The results of this study indicate that Chinese bibliometric databases, or a combination of WoS and Chinese bibliometric databases, should be used to evaluate Chinese research performance except in the few disciplines in which Chinese research performance could be assessed using WoS only.

Suggested Citation

  • Fei Shu & Charles‐Antoine Julien & Vincent Larivière, 2019. "Does the web of science accurately represent chinese scientific performance?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 70(10), pages 1138-1152, October.
    • Handle: RePEc:bla:jinfst:v:70:y:2019:i:10:p:1138-1152
    DOI: 10.1002/asi.24184
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    Cited by:

    1. Vanessa Sandoval-Romero & Vincent Larivière, 2020. "The national system of researchers in Mexico: implications of publication incentives for researchers in social sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 99-126, January.
    2. Fei Shu & Xiaojian Wang & Sichen Liu & Junping Qiu & Vincent Larivière, 2023. "Global impact or national accessibility? A paradox in China’s science," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 263-277, January.
    3. Junwen Zhu & Weishu Liu, 2020. "Comparing like with like: China ranks first in SCI-indexed research articles since 2018," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1691-1700, August.
    4. Kaile Gong & Ying Cheng, 2022. "Patterns and impact of collaboration in China’s social sciences: cross-database comparisons between CSSCI and SSCI," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 5947-5964, October.
    5. Bingqin Xu & David A. J. Teulon, 2022. "Combined Searches of Chinese Language and English Language Databases Provide More Comprehensive Data on the Distribution of Five Pest Thrips Species in China for Use in Pest Risk Assessment," Sustainability, MDPI, vol. 14(5), pages 1-19, March.

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