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

Carolina Navarro-Lopez, Salvador Linares-Mustaros and Carles Mulet-Forteza

SAGE Open, 2022, vol. 12, issue 2, 21582440221093366

Abstract: This paper presents a complete bibliometric analysis of Aitchison’s 1986 seminal book “The Statistical Analysis of Compositional Data.†We have set three objectives. The first is to analyze the academic structure of Aitchison’s 1986 book. Results reveals that although the work has received citations uninterruptedly since its publication, the number of these has increased very significantly over the past 4 years. This is due to the significant increase in the number of publications on the theme of “Compositional Data Analysis†in fields related to “geoscience†over the last few years. The second objective is to determine which main journals Aitchison’s book has been cited in. The results highlight that the main journals are indexed under the following WoS category: “Geosciences, Multidisciplinary†and “Ecology.†Of these, “Mathematical Geosciences†and “Computers, Geosciences†stand out. The third objective is to determine the main topics analyzed in the principal papers published by authors citing Aitchison’s book. Our results show that the keywords in the main papers to have cited Aitchison’s 1986 book originate from the geoscience field, since many of them are related to concepts directly linked to this field and refer to terms related to “biodiversity,†“geodiversity,†“geoheritage,†and “georesources.†Lastly, the analysis shows how the CoDA methodology is now in a phase of exponential growth, expanding to other fields. This implies that geoscience is becoming consolidated in the scientific literature as one of the branches of modern science that has given rise to a new mathematical theory of great impact.

Keywords: John Aitchison; bibliometrics; citation structure; journal ranking; hot topics; VOSviewer (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:12:y:2022:i:2:p:21582440221093366

DOI: 10.1177/21582440221093366

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