Delineating Feminist Studies through bibliometric analysis
Natsumi S. Shokida, Diego Kozlowski, Vincent Larivi\`ere

TL;DR
This paper introduces a novel bibliometric methodology combining NLP and manual curation to identify and analyze gender and feminist studies across diverse scientific disciplines using a large dataset from the Dimensions database.
Contribution
It presents a hybrid approach that integrates keyword search, topic modeling, and manual curation to effectively delineate interdisciplinary feminist research.
Findings
Over 1.9 million publications analyzed from 1668 to 2023
Characterization of gender studies topics, citation, and collaboration patterns
Insights into institutional and regional participation in feminist research
Abstract
The multidisciplinary and socially anchored nature of Feminist Studies presents unique challenges for bibliometric analysis, as this research area transcends traditional disciplinary boundaries and reflects discussions from feminist and LGBTQIA+ social movements. This paper proposes a novel approach for identifying gender/sex related publications scattered across diverse scientific disciplines. Using the Dimensions database, we employ bibliometric techniques, natural language processing (NLP) and manual curation to compile a dataset of scientific publications that allows for the analysis of Gender Studies and its influence across different disciplines. This is achieved through a methodology that combines a core of specialized journals with a comprehensive keyword search over titles. These keywords are obtained by applying Topic Modeling (BERTopic) to the corpus of titles and abstracts…
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Taxonomy
TopicsGender Politics and Representation · Gender Diversity and Inequality
