Trends in Women Studies, 2011-2020: A Computational Text Analysis
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Date
2023-11-17
Authors
Das, Suman
Kumar K, Manoj
Das, Anup Kumar
Tripathi, Manorama
Journal Title
Journal ISSN
Volume Title
Publisher
INFLIBNET Centre, Gandhinagar
Abstract
The interdisciplinary field of Women's Studies is manifested in diverse forms within the
educational and research landscape of Indian universities and institutions. By scrutinizing
trends and patterns in research, particularly focused in PhD theses, a comprehensive
understanding of this field's evolution can be gleaned. In India, the discipline of Women's
Studies is in a constant state of transformation, continually adapting its dimensions.
In this study, we present our findings derived from an examination of the core theses produced
over the last decade (2011-2020), exploring various facets of Women's Studies across multiple
departments. Leveraging the Shodhganga digital theses repository, we meticulously selected
1389 theses as the basis of our analysis. The analysis reveals that the southern region of
Corresponding Author: Dr. Manorama Tripathi, Email: manoramatripathi2@yahoo.com
India has exhibited the highest publication output
of these theses. To gain deeper insights into the
breadth of research topics addressed by scholars,
we employed computational text analysis techniques,
specifically employing two prominent methods:
Structural Topic Modelling (STM) and Latent
Dirichlet Allocation (LDA). These methodologies
enabled us to unravel the hierarchical arrangement
of topics and the co-occurrence patterns within the
documents.
In conclusion, our study underscores the significance and utility of Electronic Theses and
Dissertations (ETD) repositories, particularly in the context of Women's Studies in India.
These repositories not only facilitate comprehensive analysis but also provide a valuable
resource for researchers and scholars aiming to comprehend the trajectory.
Description
26th International Symposium, ETD 2023, Gandhinagar, Gujarat, 26-28 October, 2023
Keywords
Electronic Theses and Dissertations (ETD), ETDs on Women, Latent Dirichlet Allocation (LDA), Structural Topic Modelling (STM), Text Analysis, Women Studies