Citation Distribution Modeling (Lognormal/Tsallis)

Citation distribution modeling studies the statistical shape of how citations are spread across papers and uses that shape to compare impact fairly across very different fields. The pivotal result, from Filippo Radicchi, Santo Fortunato, and Claudio Castellano in 2008, is that although raw citation distributions differ enormously between disciplines, they collapse onto a single universal curve once each paper's citations are divided by the average for its field and year. This relative indicator turns an unfair comparison, a mathematics paper against a biomedicine paper, into a fair one by asking how each paper performs relative to its own field's baseline. The universal curve is well described by a lognormal form, and related work has used Tsallis or stretched-exponential and discounted-cumulative formulations, giving scientometrics a principled statistical foundation for normalization rather than ad hoc field adjustments.