A Principal Component Analysis of 39 Scientific Impact Measures

By Johan Bollen, Herbert Van de Sompel, Aric A. Hagberg, Ryan Chute. PLoS ONE, 2009

566 citations recorded by the source corpus.

Background The impact of scientific publications has traditionally been expressed in terms of citation counts. However, scientific activity has moved online over the past decade. To better capture scientific impact in the digital era, a variety of new impact measures has been proposed on the basis of social network analysis and usage log data. Here we investigate how these new measures relate to each other, and how accurately and completely they express scientific impact. Methodology We performed a principal component analysis of the rankings produced by 39 existing and proposed measures of scholarly impact that were calculated on the basis of both citation and usage log data. Conclusions Our results indicate that the notion of scientific impact is a multi-dimensional construct that can not be adequately measured by any single indicator, although some measures are more suitable than others. The commonly used citation Impact Factor is not positioned at the core of this construct, but at its periphery, and should thus be used with caution.

Subfields: Information Systems, Information Systems and Management, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/bf607ae03187059fe38779aab0953853ce5a90fb

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Citations in the corpus

Self-Selected or Mandated, Open Access Increases Citation Impact for Higher Quality Research (2010, background): “And even after the competitive advantage is gone because all articles are OA, the download advantage will continue to be enjoyed by all articles [36,37] (thereby potentially influencing research even where it does not generate citations), while the quality advantage will see to it that for the best ”
A network DEA quantity and quality-orientated production model: An application to Australian university research services (2016, methodology): “Recent studies using the SJR include [48], who used it as a tool for evaluating journals in the Scopus database, [49], who compared the SJR with the Thomson Scientific impact factor, and [50], who grouped the impact factor and the SJR together to examine both bibliometric and usage indicators.”
A review of the literature on citation impact indicators (2015, methodology): “citation impact indicators for journals are reported by Bollen et al. (2009), Leydesdorff (2009), and Elkins et al. (2010).”