A Principal Component Analysis of 39 Scientific Impact Measures

Journal Article · 29 June 2009 · PLoS ONE

DOI: https://doi.org/10.1371/journal.pone.0006022 · OSTI ID:1627376

Bollen, Johan ^[1]; Van de Sompel, Herbert ^[2]; Hagberg, Aric ^[2]; Chute, Ryan ^[2]

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1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States); DOE/OSTI
2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

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.

• Research Organization: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
• Sponsoring Organization: Andrew W. Mellon Foundation; USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division
• OSTI ID: 1627376
• Journal Information: PLoS ONE, Journal Name: PLoS ONE Journal Issue: 6 Vol. 4; ISSN 1932-6203
• Publisher: Public Library of ScienceCopyright Statement
• Country of Publication: United States
• Language: English