Finding rising stars in bibliometric networks

Ali Daud (), Min Song (), Malik Khizar Hayat (), Tehmina Amjad (), Rabeeh Ayaz Abbasi (), Hassan Dawood () and Anwar Ghani ()
Additional contact information
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

Scientometrics, 2020, vol. 124, issue 1, No 26, 633-661

Abstract: 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.

Keywords: Finding rising stars (FRS); Ranking; Prediction; Clustering; Analysis; Bibliometric networks (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11192-020-03466-w

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