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 production and impact 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. 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 similar to 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.

Statistical regularities in the rank-citation profile of scientists

Succi Sauro
2011

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 production and impact 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. 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 similar to 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.
2011
Istituto Applicazioni del Calcolo ''Mauro Picone''
Bibliometrics
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/312467
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