Predicting the Q of junior researchers using data from the first years of publication

Antônio de Abreu Batista-, Fábio Castro Gouveia and Jesús P. Mena-Chalco

Journal of Informetrics, 2021, vol. 15, issue 2

Abstract: A researcher's Q denotes their ability in scientific research as a real number. Due to their short presence in the academic environment, junior researchers have unstable Q values. This article aims to present a model that uses data from junior researchers’ first years of publication to predict their stable Q values. We tested the deep model and the linear regression model and compared their accuracies. We have obtained reliable results showing that the predicted values estimated with both models are better than the estimated Q values computed with the Q model itself when using only data from the first five years of publication. Lastly, we note that both approaches are robust approaches to deal with the inflation of citation bias.

Keywords: Junior researcher; Research performance; Deep learning; Linear regression (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:15:y:2021:i:2:s1751157721000018

DOI: 10.1016/j.joi.2021.101130

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