Statistical regularities in the rank-citation profile of scientists

TL;DR

This paper investigates the statistical regularities in individual scientists' impact profiles, revealing how impact measures like the h-index and a new scaling parameter etaiffer among scientists and can serve as benchmarks for career modeling.

Contribution

It introduces a new scaling parameter eta alongside the h-index to better quantify individual impact profiles and demonstrates their relationship with total citations.

Findings

Impact profiles fit a common distribution with two scaling exponents.

The impact scaling parameter eta differentiates scientists with similar h-indices.

Total citations scale as h^{1+eta}.

Abstract

Recent "science of science" research shows that scientific impact measures for journals and individual articles have quantifiable regularities across both time and discipline. However, little is known about the scientific impact distribution at the scale of an individual scientist. We analyze the aggregate scientific production and impact of individual careers using the rank-citation profile c_{i}(r) of 200 distinguished professors and 100 assistant professors. For the entire range of paper rank r, we fit each c_{i}(r) to a common distribution function that is parameterized by two scaling exponents. Since two scientists with equivalent Hirsch h-index can have significantly different c_{i}(r) profiles, our results demonstrate the utility of the \beta_{i} scaling parameter in conjunction with h_{i} for quantifying individual publication impact. We show that the total number of citations C_{i} tallied from a scientist's N_{i} papers scales as C_{i} \sim h_{i}^{1+\beta_{i}}. Such statistical regularities in the input-output patterns of scientists can be used as benchmarks for theoretical models of career progress.