Measuring researcher independence using bibliometric data: A proposal for a new performance indicator

Abstract

Bibliometric indicators are increasingly used at the individual level -as is exemplified by the popularity of the H-index and many other publication and citation based indicators used in evaluation. The issue isn't whether these indicators can be considered useful, as they do provide a description of a researcher's oeuvre. However, at the same time, they are not enough to assess the quality of a researcher and his/her oeuvre: Quality has more dimensions than productivity and impact alone. In this paper, we argue that independence is an equally important characteristic that however lacks validated indicators for measuring it at the individual level. We propose two indicators to measure different dimensions of independence: one assessing whether a researcher has developed an own collaboration network, and another assessing the level of thematic independence. We illustrate how these indicators distinguish between researchers that are equally productive and have similar impact. The independence indicator is a step forward in evaluating individual scholarly quality: in cases where citations and publications do not distinguish, the indicators for independence may do.

Bibliometrics of Scientific Articles on Solid Waste Management in Shopping Malls (1999–2020)

“…The bibliometric indicators estimate the quality and number of publications [28,29]. The keywords WASTE, MANAGEMENT, INDICATOR, and MALLAND SHOPPING CENTER were used as the search criteria.…”

A Comparative Analysis of Scopus and Web of Science (WoS) Literature on the Autism Crisis

“…Our first approach was to choose the quality dimensions. The most used quality dimensions relevant for assessing a researcher are productivity and impact; there are other metrics as an independence indicator (Van den Besselaar and Sandström 2018) too. There are some reviews, even from the tools themselves (Moral-Muñoz et al 2020), where Bibliometrix seems an optimal tool for our analysis because it is an open source R package for performing comprehensive SMA (Science Map Analysis) (Aria & Cuccurullo, 2017) and openness was our first step.…”

The impact of preprint servers in the formation of novel ideas

“…A number of studies propose different ideas to quantify originality in science and technology (Cozzens et al, 2010;Alexander et al, 2013;Rzhetsky et al, 2015;Rotolo et al, 2015;Wang and Chai, 2018;Shibayama and Wang, 2020) or their impact on the other works (Shi et al, 2010;Shahaf et al, 2012;Sinatra et al, 2016;Hutchins et al, 2016;Wesley-Smith et al, 2016;Herrmannova et al, 2018b,a;Zhao et al, 2019;Bornmann et al, 2019;Small et al, 2019). The prediction of breakthroughs, scientific impact and citation counts is a well developed area (Schubert and Schubert, 1997;Garfield et al, 2002;Dietz et al, 2007;Lokker et al, 2008;Shi et al, 2010;Uzzi et al, 2013;Alexander, 2013;Klimek et al, 2016;Tahamtan et al, 2016;McKeown et al, 2016;Clauset et al, 2017;Peoples et al, 2017;Salatino et al, 2018;Dong et al, 2018;Iacopini et al, 2018;Feldman et al, 2018;van den Besselaar and Sandström, 2018;Klavans et al, 2020). However, the question asked in these works is different from the one we ask.…”