Universality of citation distributions: Toward an objective measure of scientific impact

By Filippo Radicchi, Santo Fortunato, Claudio Castellano. Proceedings of the National Academy of Sciences of the United States of America, 2008

818 citations recorded by the source corpus.

We study the distributions of citations received by a single publication within several disciplines, spanning broad areas of science. We show that the probability that an article is cited c times has large variations between different disciplines, but all distributions are rescaled on a universal curve when the relative indicator cf = c/c0 is considered, where c0 is the average number of citations per article for the discipline. In addition we show that the same universal behavior occurs when citation distributions of articles published in the same field, but in different years, are compared. These findings provide a strong validation of cf as an unbiased indicator for citation performance across disciplines and years. Based on this indicator, we introduce a generalization of the h index suitable for comparing scientists working in different fields.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/1ead99845d1dc1c0d58e47eda9ba21aa0234878f

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Citations in the corpus

h-Index: A review focused in its variants, computation and standardization for different scientific fields (2009, background): “Finally, Radicchi et al. (2008) study the distributions of citations received by a single publication within several disciplines, spanning broad areas of science.”
A multilevel modelling approach to investigating the predictive validity of editorial decisions: do the editors of a high profile journal select manuscripts that are highly cited after publication? (2011, background): “Radicchi et al. (2008) found, for example, that papers in general biology (the subject category of the journal where the paper appears; see Thomson Reuters) are cited on average 14.6 times, whereas papers in developmental biology are cited on average 38.7 times (see here also Bornmann and Daniel…”
The Matthew effect in empirical data (2014, background): “There are, however, a number of other socio-technical [57, 73–76, 78–81] and biological [61, 63] networks, where the availability of time-resolved data allowed testing for the Matthew effect.”
Algorithmic stemmers or morphological analysisq An evaluation (2009, background): “Radicchi et al. (2008) present two figures to show a comparison of the distributions of citation rates and cf”
Reputation and impact in academic careers (2013, background): “[1] Radicchi F, Fortunato S & Castellano C (2008) Universality of”
A review of the literature on citation impact indicators (2015, background): “Radicchi et al. (2008) conclude that normalization based on the ratio of the actual and the expected number of citations of a publication indeed yields the desired universality of citation distributions.”
Quantifying Long-Term Scientific Impact (2013, methodology): “of a scientific discovery, remains an elusive task. In the past, much attention has focused on citation distributions, with debates on whether they follow a power law (2, 18, 19) or a log-normal form (3, 7, 15). Also, universality across disciplines allowed the rescaling of the distributions by disc”
Methods for detrending success metrics to account for inflationary and deflationary factors* (2011, neutral): “Analogous eﬀorts are taking place in the bibliometric sciences in order to establish universal citation metrics which account for variations across time and academic discipline [39, 43].”
The science of science: from the perspective of complex systems (2017, background): “proposed a relative index cf = c/c0 and found that the distribution of cf of papers in various disciplines in the same year overlap in a single curve that resembles a log-normal distribution [31].”
Defining and identifying Sleeping Beauties in science (2015, background): “Several factors can potentially affect the amount of citations accumulated by a paper over time, including its quality, timeliness, and potential to trigger further inquiries (9), the reputation of its authors (16, 17), as well as its topic and age (8).”
Relative Citation Ratio (RCR): A New Metric That Uses Citation Rates to Measure Influence at the Article Level (2015, background): “” (E) Comparison of RCRs (orange) and Thompson Reuters ratios (blue) [17,28] for the same 544 articles with a low denominator.”