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Age Structures of Scientific Collaboration in Chinese Computer Science

Author

Listed:
  • Liming Liang

    (Henan Normal University)

  • Hildrun Kretschmer

    (Free University)

  • Yongzheng Guo

    (Henan Normal University)

  • Donald Beaver

    (Williams College)

Abstract

This paper is a scientometric study of the age structure of scientific collaboration in Chinese computer science. Analysis reveals some special age structures in scientific collaboration in Chinese computer science. Most collaborations are composed of scientists younger than thirty-six (Younger) or older than fifty (Elder). For two-dimensional collaboration formed by first and second authors, Younger-Elder and Younger-Younger are the predominant age structures. For three-dimensional collaboration formed by first, second and third authors, Younger-Younger-Elder and Younger-Younger-Younger are the most important age structures. Collaboration between two authors older than 38 amounts to only 6.4 percent of all two-person collaborations. Collaboration between two middle-aged scientists is seldom seen. Why do such types of age structure in Chinese computer science exist? We suggest a tentative explanation based on analyses of the age composition of all authors, the age distributions of the authors in different ranks, and the name-ordering of authors in articles written by professors and their students.

Suggested Citation

  • Liming Liang & Hildrun Kretschmer & Yongzheng Guo & Donald Beaver, 2001. "Age Structures of Scientific Collaboration in Chinese Computer Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 52(3), pages 471-486, November.
    • Handle: RePEc:spr:scient:v:52:y:2001:i:3:d:10.1023_a:1014252017971
    DOI: 10.1023/A:1014252017971
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    References listed on IDEAS

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    1. Katz, J. Sylvan & Martin, Ben R., 1997. "What is research collaboration?," Research Policy, Elsevier, vol. 26(1), pages 1-18, March.
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    Cited by:

    1. Fuyuki Yoshikane & Takayuki Nozawa & Susumu Shibui & Takafumi Suzuki, 2009. "An analysis of the connection between researchers’ productivity and their co-authors’ past attributions, including the importance in collaboration networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 79(2), pages 435-449, May.
    2. Benjamin Clark, 2011. "Influences and conflicts of federal policies in academic–industrial scientific collaboration," The Journal of Technology Transfer, Springer, vol. 36(5), pages 514-545, October.
    3. Zhigang Hu & Chaomei Chen & Zeyuan Liu, 2014. "How are collaboration and productivity correlated at various career stages of scientists?," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1553-1564, November.
    4. Frandsen, Tove Faber & Nicolaisen, Jeppe, 2010. "What is in a name? Credit assignment practices in different disciplines," Journal of Informetrics, Elsevier, vol. 4(4), pages 608-617.
    5. Liming Liang & Lixin Chen & Yishan Wu & Junpeng Yuan, 2012. "The role of Chinese universities in enterprise–university research collaboration," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(1), pages 253-269, January.
    6. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
    7. Liming Liang & Junwan Liu & Ronald Rousseau, 2004. "Name order patterns of graduate candidates and supervisors in Chinese publications: A case study of three major Chinese universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 61(1), pages 3-18, September.
    8. Liming Liang & Yongzheng Guo & Mari Davis, 2002. "Collaborative patterns and age structures in Chinese publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(3), pages 473-489, July.
    9. Bozeman, Barry & Corley, Elizabeth, 2004. "Scientists' collaboration strategies: implications for scientific and technical human capital," Research Policy, Elsevier, vol. 33(4), pages 599-616, May.

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