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Understanding the advisor–advisee relationship via scholarly data analysis

Author

Listed:
  • Jiaying Liu

    (Dalian University of Technology)

  • Tao Tang

    (University of Electronic Science and Technology of China)

  • Xiangjie Kong

    (Dalian University of Technology)

  • Amr Tolba

    (King Saud University
    Menoufia University)

  • Zafer AL-Makhadmeh

    (King Saud University)

  • Feng Xia

    (Dalian University of Technology)

Abstract

Advisor–advisee relationship is important in academic networks due to its universality and necessity. Despite the increasing desire to analyze the career of newcomers, however, the outcomes of different collaboration patterns between advisors and advisees remain unknown. The purpose of this paper is to find out the correlation between advisors’ academic characteristics and advisees’ academic performance in Computer Science. Employing both quantitative and qualitative analysis, we find that with the increase of advisors’ academic age, advisees’ performance experiences an initial growth, follows a sustaining stage, and finally ends up with a declining trend. We also discover the phenomenon that accomplished advisors can bring up skilled advisees. We explore the conclusion from two aspects: (1) Advisees mentored by advisors with high academic level have better academic performance than the rest; (2) Advisors with high academic level can raise their advisees’ h-index ranking. This work provides new insights on promoting our understanding of the relationship between advisors’ academic characteristics and advisees’ performance, as well as on advisor choosing.

Suggested Citation

  • Jiaying Liu & Tao Tang & Xiangjie Kong & Amr Tolba & Zafer AL-Makhadmeh & Feng Xia, 2018. "Understanding the advisor–advisee relationship via scholarly data analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 161-180, July.
    • Handle: RePEc:spr:scient:v:116:y:2018:i:1:d:10.1007_s11192-018-2762-2
    DOI: 10.1007/s11192-018-2762-2
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    References listed on IDEAS

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