| By: |
Michał Brzeziński (Faculty of Economic Sciences, University of Warsaw) |
| Abstract: |
Modeling distributions of citations to scientific papers is crucial for
understanding how science develops. However, there is a considerable empirical
controversy on which statistical model fits the citation distributions best.
This paper is concerned with rigorous empirical detection of power-law
behaviour in the distribution of citations received by the most highly cited
scientific papers. We have used a large, novel data set on citations to
scientific papers published between 1998 and 2002 drawn from Scopus. The
power-law model is compared with a number of alternative models using a
likelihood ratio test. We have found that the power-law hypothesis is rejected
for around half of the Scopus fields of science. For these fields of science,
the Yule, power-law with exponential cut-off and log-normal distributions seem
to fit the data better than the pure power-law model. On the other hand, when
the power-law hypothesis is not rejected, it is usually empirically
indistinguishable from most of the alternative models. |
| Keywords: |
power law, Pareto model, citation distribution, bibliometrics, scientometrics, Scopus, model selection |
| JEL: |
A12 C46 C52 |
| Date: |
2014 |
| URL: |
https://d.repec.org/n?u=RePEc:war:wpaper:2014-05 |