Scaling and Kinetic Exchange Like Behavior of Hirsch Index and Total Citation Distributions: Scopus-CiteScore Data Analysis
arXiv:2301.09528 · doi:10.1016/j.physa.2023.129061
Abstract
We analyze the data distributions , ) and of the Hirsch index , total citations () and total number of papers () of the top scoring 120,000 authors (scientists) from the Stanford cite-score (or c-score) 2022 list and their corresponding (), ) and () statistics from the Scopus data. For reasons explained in the text, we divided the data of these top scorers (c-scores in the range 5.6125 to 3.3461) into six successive equal-sized Groups of 20,000 authors or scientists. We tried to fit, in each Group, , and with Gamma distributions, viewing them as the ``wealth distributions'' in the fixed saving-propensity kinetic exchange models and found with fitting noise level or temperature level () and average value of , and the power determined by the ``citation saving propensity'' in each Group. We further showed that using some earlier proposed power law scaling like (or ) with , we can derive the observed from the observed or , with , but depending on the Group considered. This observation suggests that the average citations per paper () in each group () vary (from 58 to 29) with the c-score range of the six Groups considered here, implying different effective Dunbar-like coordination numbers of the scientists belonging to different groups or networks.
Accepted for publication in Physica A