Authorship pattern and applicability of Lotka’s law in heart transplantation research: A bibliometric review using R-tool
DOI:
https://doi.org/10.34256/Keywords:
Heart Transplantation, Bibliometric Analysis, Authorship Pattern, Lotka’s Law, K-S test, Bibliometrix R-toolAbstract
The study aimed to analyse author productivity, authorship trends, and the applicability of Lotka's law in heart transplantation research from 1994 to 2023, and to propose guidance for future research. A total of 49791 publications on heart transplantation retrieved by the Scopus database were used for the study. This paper uses Bibliometrix and Biblioshiny to analyse and report relevant data. Based on the bibliometric analysis, we identified descriptive statistics for the overall dataset, the most prolific authors with high dominance, metrics for highly influential authors, and the distribution of authorship patterns in accordance with Lotka's law. The study outcomes reveal that the 'n' (-2.22137), constant 'C' (0.00169), and CV (0.0480552) play an important role in the predictive value of Lotka's law estimation. The value of Dmax (0.6398) is computed from the cumulative frequency of observed and expected authors, and the Chi-square (X2=1259.019) value is also included to strengthen Lotka's law. Among the 114945 authors, the distribution of authorship is as follows: 64.376% of authors published one article; 14.530% of authors published two; 6.431% of authors published three; and 10.814% of authors published up to ten articles. However, the proportions should be 60.793%, 15.198%, 6.755%, and 11.471%, respectively, as per Lotka's law for the current dataset. The study attempts to validate the authorship patterns in heart transplantation research using the Kolmogorov-Smirnov (K-S) and Chi-square tests. It found that the goodness-of-fit tests rejected the null hypothesis; hence, the inverse-square of Lotka did not fit the heart transplantation dataset.
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