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Finding rising stars in bibliometric networks

Author

Listed:
  • Ali Daud

    (University of Jeddah)

  • Min Song

    (Yonsei University)

  • Malik Khizar Hayat

    (IIU)

  • Tehmina Amjad

    (IIU)

  • Rabeeh Ayaz Abbasi

    (QAU)

  • Hassan Dawood

    (University of Engineering and Technology)

  • Anwar Ghani

    (IIU)

Abstract

Finding rising stars (FRS) is a hot research topic investigated recently for diverse application domains. These days, people are more interested in finding people who will become experts shortly to fill junior positions than finding existing experts who can immediately fill senior positions. FRS can increase productivity wherever they join due to their vibrant and energetic behavior. In this paper, we assess the methods to find FRS. The existing methods are classified into ranking-, prediction-, clustering-, and analysis-based methods, and the pros and cons of these methods are discussed. Details of standard datasets and performance-evaluation measures are also provided for this growing area of research. We conclude by discussing open challenges and future directions in this prosperous area of research.

Suggested Citation

  • Ali Daud & Min Song & Malik Khizar Hayat & Tehmina Amjad & Rabeeh Ayaz Abbasi & Hassan Dawood & Anwar Ghani, 2020. "Finding rising stars in bibliometric networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 633-661, July.
    • Handle: RePEc:spr:scient:v:124:y:2020:i:1:d:10.1007_s11192-020-03466-w
    DOI: 10.1007/s11192-020-03466-w
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    References listed on IDEAS

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    Cited by:

    1. Matthias Kuppler, 2022. "Predicting the future impact of Computer Science researchers: Is there a gender bias?," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6695-6732, November.
    2. Tehmina Amjad & Javeria Munir, 2021. "Investigating the impact of collaboration with authority authors: a case study of bibliographic data in field of philosophy," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4333-4353, May.

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