Researcher influence prediction (ResIP) using academic genealogy network

Dhananjay Kumar, Plaban Kumar Bhowmick and Jiaul H Paik

Journal of Informetrics, 2023, vol. 17, issue 2

Abstract: In academia researchers join a research community over time and contribute to the advancement of a field in a variety of ways. One of the most established ways to contribute to the field is by passing on knowledge to the future generations through academic advising. Many academic scholars have more influence, while others fail to make an impact. Typically, academic influence refers to the ability of a researcher to pass on her/his “academic gene” in future researchers. In this article, we propose the task of Researcher Influence Prediction (ResIP) to predict researchers’ future influence in an academic field through the analysis of the corresponding academic genealogy network. Researcher influence prediction has got several implications as far as different academic outcomes are concerned (e.g. funding, awards, career progression, collaboration, identifying prolific researchers etc.).

Keywords: Influence prediction; Academic genealogy network; Deep learning; Advisor-advisee relationship; Lineage growth prediction (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:17:y:2023:i:2:s1751157723000172

DOI: 10.1016/j.joi.2023.101392

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