Woman Leadership 10 years: Topic modeling and Computational Grounded Theory Approach

Final analysis complated

Author

Chungil Chae

Published

Thu, 5 March 2026

Synthesis and Revisiting Korean Women Leaders’ Narrative: A Computational Analysis Using Structural Topic Modeling

Chad

Abstract

Over the past eight years, we have conducted eight qualitative studies on women leaders in South Korea (Korea) from the lens of work-life balance and career and leadership development, using semi-structured interviews. Given the women leaders’ 200 narratives, we felt a strong need to reanalyze the interview data to tackle the subjectivity issue in qualitative research using topic modeling that is a computational technique to mining a large volume of texts. The purpose of this study, therefore, was to reanalyze women leaders’ narratives and to examine the research themes identified through a computational analysis. As a result, we identified key research topics on Korean women leaders’ narratives, compared those with the research themes from the previous qualitative studies, and provide implications for HRD research and practice for the future.

Planning

Schedule

  • In March, complate a draft
  • In April, review and revision, then submit

Progress

  • Analysis Done

Authorship and Authors

Author Contribution

  • Supervision: Yoonjoo Cho
  • Project administration: Yoonjoo Cho
  • Conceptualization: Chungil (Chad) Chae
  • Data accusation: Yoonjoo Cho
  • Data curation: Chungil (Chad) Chae, Sumi Lee
  • Formal analysis:
    • Chungil (Chad) Chae
  • Investigation:
    • Yoonjoo Cho, Jieun You, Sumi Lee
  • Methodology:
    • Chungil (Chad) Chae
  • Resources: Yoonjoo Cho
  • Validation: Yoonjoo Cho, Jieun You, Sumi Lee, Chungil Chae
  • Visualization: Chungil Chae
  • Writing – original draft: Chungil Chae, Yoonjoo Cho, Jieun You, Sumi Lee
  • Writing – review & editing: Yoonjoo Cho, Jieun You, Sumi Lee, Chungil Chae

Authors

Yonjoo Cho

University of Texas at Tyler

Chungil Chae, Ph.D., M.S.

Chungil Chae (Chad), Ph.D., is an Assistant Professor in Business Analytics at Wenzhou-Kean University, specializing in data analytics, human resource development, and knowledge-sharing in multinational organizations. With a Ph.D. from Pennsylvania State University, his research integrates business intelligence, workforce education, and computational social science. Dr. Chae has an extensive publication record in top-tier journals and has received multiple academic awards, including the Outstanding Paper in the Emerald Literati Awards. He has held positions as a post-doctoral scholar at Penn State and has contributed to various funded research projects in cognitive science and business analytics. His expertise extends to teaching business analytics, data mining, and management courses while actively engaging in curriculum development and academic service.

Jieun You

Valdosta State University

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Sumi Lee

University of Georgia

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Acknowledgement

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Declearation

IRB

Funding

AI