Quantifying the dynamics of nearly 100 years of dominance hierarchy research

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1098/rstb.2020.0433. This is version 2 of this Preprint.

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Authors

Elizabeth A. Hobson

Abstract

Dominance hierarchies have been studied for almost 100 years. A science of science approach can help provide high-level insight into how the dynamics of dominance hierarchy research have shifted or been maintained over this long timescale. To summarize these general patterns, I extracted publication metadata using a Google Scholar search of "dominance hierarchy, resulting in over 26,000 publications. I used text mining approaches to assess patterns in three areas: (1) general patterns in publication frequency and rate, (2) dynamics of term usage, and (3) term co-occurrence in publications across the history of the field. While the overall number of publications per decade continues to rise, the percent growth rate has fallen in recent years, demonstrating that although there is sustained interest in dominance hierarchies, the field is no longer experiencing the explosive growth it showed in earlier decades. Based on term co-occurrence networks and community structure, the different subfields of dominance hierarchy research were most strongly separated early in the fields history while modern research shows more evidence for cohesion and a lack of distinct term community boundaries. These methods provide a general view of the history of research on dominance hierarchies and can be applied to other fields or search terms to gain broad synthetic insight into patterns of interest, especially in fields with large bodies of literature.

DOI

https://doi.org/10.32942/osf.io/4hgkb

Subjects

Biology, Integrative Biology, Life Sciences

Keywords

dominance hierarchy, Science of science, Text Mining

Dates

Published: 2021-07-19 14:27

Last Updated: 2021-10-21 14:17

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License

CC-BY Attribution-No Derivatives 4.0 International

Additional Metadata

Data and Code Availability Statement:
All data and code will be released once the paper is published