Volume 18, No. 6, 2021

Application Of Scientometric Laws On Deep Learning Research Output Using R Programming

M.Thamaraiselvi , Dr. S. Lakshmi


The present study investigates the validity of Lotka’s law, Bradford’s law and Zipf’s law on deep learning research publications using R programming. Data was collected from SCOPUS database for the period of four years from 2017 to 2020. A total of 28536 records were retrieved from the database during the study period. The findings of the study shows that single author dominated in the field of deep learning research with 77.40% of total publications. Lotka’s law of scientific productivity of authors reveals that 14.32% of publications was contributed by single author which is less than 60% of author productivity, Bradford's law of journals are scattered as 76:766:5019 in three zones and Zipf’s law indicates that deep learning is the word secured top rank in frequency of occurrence. The result also concluded that the application of Lotka’s law and Zipf’s law are did not fit to the dataset whereas Bradford’s law is fit to the deep learning research output.

Pages: 5683-5694

Keywords: Deep learning, Lotka’s law, Bradford’s law, Zipf’s law, R programming, Scientometrics, SCOPUS.

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