The Distribution of the Asymptotic Number of Citations to Sets of Publications by a Researcher or from an Academic Department Are Consistent with a Discrete Lognormal Model

Abstract

How to quantify the impact of a researcher’s or an institution’s body of work is a matter of increasing importance to scientists, funding agencies, and hiring committees. The use of bibliometric indicators, such as the h-index or the Journal Impact Factor, have become widespread despite their known limitations. We argue that most existing bibliometric indicators are inconsistent, biased, and, worst of all, susceptible to manipulation. Here, we pursue a principled approach to the development of an indicator to quantify the scientific impact of both individual researchers and research institutions grounded on the functional form of the distribution of the asymptotic number of citations. We validate our approach using the publication records of 1,283 researchers from seven scientific and engineering disciplines and the chemistry departments at the 106 U.S. research institutions classified as “very high research activity”. Our approach has three distinct advantages. First, it accurately captures the overall scientific impact of researchers at all career stages, as measured by asymptotic citation counts. Second, unlike other measures, our indicator is resistant to manipulation and rewards publication quality over quantity. Third, our approach captures the time-evolution of the scientific impact of research institutions.

And, not or: Quality, quantity in scientific publishing

“…In particular, because citation distributions have been observed to be log-normal [20], we take the log of the number of citations plus one. We analyze nearly 200,000 publications by more than 1600 members of the National Academy of Sciences between 1980 and 2006.…”

Hot streaks in artistic, cultural, and scientific careers

“…Many factors are known to influence the collective impact of a career, ranging from productivity 15,22,34 to citation disparity and dynamics 17,18,21,25,27,35 to temporal inhomogeneities along a career 14,[22][23][24][25]36 .…”

Data-driven predictions in the science of science

“…Although the relative timing of each scientist's own highest-impact paper may be impossible to predict, predicting how many citations that paper will attract is a different matter (17,18). Specifically, citations to published papers vary across scientists in a systematic and persistent way that correlates with the visibility of a scientist's body of work but that is independent of the field of study.…”