Publication Date

9-13-2025

Document Type

Article

Publication Title

Journal of Academic Librarianship

Volume

51

Issue

6

DOI

10.1016/j.acalib.2025.103142

Abstract

This study applies critical bibliometric methods to the library science literature published from 2019 to early 2025. It combines citation network analysis and text analysis in novel ways to identify clusters of articles focused on trends and practice areas, and to analyze the citation rates and centrality of those clusters within the network of library science articles. The study provides an example of how critical bibliometric methods can be applied to provide context and nuance when assessing the impact of research and interpreting research impact metrics. Themes identified within the literature include the COVID-19 pandemic, diversity, artificial intelligence, and social media, and the study notes differences in citation rates between these trends, with articles in the cluster focused on diversity cited at a lower rate than those focused on technology. While the study employs a novel weighting method to mitigate the impact of journal self-citation, the preliminary results demonstrate the susceptibility of citation-based metrics to gaming by authors, journal editors, and publishers. Critical bibliometric methods, like those used in this study can illuminate flaws and biases in widely-accepted bibliometric approaches, and point towards unanswered questions about our perceptions of prestige, quality, and impact in academic research.

Keywords

Citation network analysis, Critical bibliometrics, Critical data studies, Research impact, Scholarly communication, Text analysis

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Department

Library

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