Exploring the Evolution of Bibliometric Analysis: A Comprehensive Study of Scientific Publications from 1974 to 2024 Using the Dimensions AI Database

Authors

  • Vinayak P. Hakkaraki Karnataka State Law University, Hubballi, Karnataka, India

DOI:

https://doi.org/10.70112/ajist-2024.14.1.3878

Keywords:

Bibliometrics, Bibliometric Literature, Scientific Mapping, Dimensions AI, Bibliometric Analysis, Public Health

Abstract

Bibliometrics is the practice of analyzing books, articles, and other publications using statistical methods, with a particular focus on scientific contexts. This research employs bibliometric analysis to explore the evolution of the research landscape on bibliometrics and bibliometric analysis literature, utilizing the Dimensions AI database. A total of 23,527 articles were discovered in the Dimensions AI database when the search terms “bibliometric” and “bibliometric analysis” were input into the “Title” field. These articles cover a range of publication years from 1974 to 2024. Furthermore, upon selecting the “Health Science” category, 2,011 articles were displayed. Co-occurrence, co-authorship, countries, academic institutions, and future orientations are used to illustrate previous trends, growth, and prospects in the results, which are displayed through graphs, tables, and data maps. The results show that papers account for the majority of publications (1,888), with preprints coming in second (93). The most productive journal is Frontiers in Public Health, with 109 articles and 659 citations, while the most productive author is Waleed Mohamad Sweileh, with a substantial number of publications (n = 36) and total citations (1,428). The most productive academic institution is An-Najah National University, which tops the list with 63 publications and 2,082 citations.

Downloads

Published

20-03-2024

How to Cite

Hakkaraki, V. P. (2024). Exploring the Evolution of Bibliometric Analysis: A Comprehensive Study of Scientific Publications from 1974 to 2024 Using the Dimensions AI Database. Asian Journal of Information Science and Technology, 14(1), 24–31. https://doi.org/10.70112/ajist-2024.14.1.3878