A Bibliometric Analysis of the 35th anniversary of the paper "The Statistical Analysis of Compositional Data" by John Aitchison (1982)

Abstract

This study presents a comprehensive bibliometric analysis of the paper published by John Aitchison in the Journal of the Royal Statistical Society. Series B (Methodological) in 1982. Having recently reached the milestone of 35 years since its publication, this pioneering paper was the first to illustrate the use of the methodology "Compositional Data Analysis" or "CoDA". By October 2019, this paper had received over 780 citations, making it the most widely cited and influential article among those using said methodology. The bibliometric approach used in this study encompasses a wide range of techniques, including a specific analysis of the main authors and institutions to have cited Aitchison' paper. The VOSviewer software was also used for the purpose of developing network maps for said publication. Specifically, the techniques used were co-citations and bibliographic coupling. The results clearly show the significant impact the paper has had on scientific research, having been cited by authors and institutions that publish all around the world.

“The Statistical Analysis of Compositional Data” by John Aitchison (1986): A Bibliometric Overview

“…A further limitation is that the results are dynamic and will inevitably change over time. Despite these limitations of our analysis, we consider that this paper can be regarded as an overview of the relationships that occur between Aitchison's book and the geoscience field, as well as modern science, expanding on what is already known about the beginnings of CoDA in journals (Navarro et al, 2021).…”

Bibliometric Foundations: Tracking the Footprint of Green Finance and Financial Institutions in Global Research

“…VOSviewer and the bibliometric packages available in R-Studio offer a wide range of functionalities beyond basic data management. These tools enable users to generate visual representations, such as co-authorship networks, co-citation maps, and keyword landscapes, aiding in the visualization of scholarly landscapes and trends (Navarro et al, 2021;Saenz Tovar & Alejandro Reta, 2022). Additionally, they support complex analyses like identifying research hotspots, uncovering collaborations among authors or institutions, and assessing the impact of scholarly work within a field (Moral-Muñoz et al, 2020;Whitlock et al, 2019).…”