@article{ART003281420},
author={Jo, Seong-min and Park, Ha-na and Lee, Hye-Eun and Shin, Dong-hee},
title={An Analysis of Research Trends in ‘The Journal of Asian Women’ Using Text Mining},
journal={아시아여성연구},
issn={1225-9241},
year={2025},
volume={64},
number={3},
pages={197-229},
doi={10.14431/jaw.2025.12.64.3.197}
TY - JOUR
AU - Jo, Seong-min
AU - Park, Ha-na
AU - Lee, Hye-Eun
AU - Shin, Dong-hee
TI - An Analysis of Research Trends in ‘The Journal of Asian Women’ Using Text Mining
JO - 아시아여성연구
PY - 2025
VL - 64
IS - 3
PB - Research Institute of Asian Women
SP - 197
EP - 229
SN - 1225-9241
AB - This paper is This paper examines research trends in research trends in Korean women’s studies women’s studies by applying text mining techniques to articles published in The Journal of Asian Women from 2006 to 2025. A total of 267 articles were collected, and their titles, abstracts, and keywords were analyzed. First, the results of the word frequency analysis indicate that broadly shared social issues in women’s studies—such as men, migration, marriage, and policy—emerged as high-frequency keywords. In contrast, TF-IDF analysis highlighted more distinctive topics specific to individual studies, including hwa-byung, scientists, menopause, and concentration camps. Second, LDA topic modeling identified eight major topics: (1) women’s career development and workplace experiences; (2) gender inequality and labor and social policies; (3) representations of war, colonial experiences, and gender-based violence; (4) migration, multiculturalism, and the international diffusion of gender policies; (5) family, patriarchy, and gender policy; (6) cultural discourses on family, relationships, and gendered experiences; (7) family formation and the agency of marriage migrant women; and (8) educational, activist, and political practices of gender citizenship. Third, time-series analysis of topic proportions shows that themes related to labor, policy, and citizenship temporarily surged during specific periods and subsequently dispersed, whereas topics concerning multiculturalism, family, and marriage maintained relatively stable proportions across the entire period. Simple linear regression analysis further reveals that none of the topics exhibited statistically significant increasing or decreasing trends, indicating an overall neutral pattern. These findings suggest that research topics in The Journal of Asian Women have not converged toward a single dominant direction but have instead been recurrently revisited and reconfigured in response to changing social contexts and policy demands.
KW - The Journal of Asian Women;Research Trends;Text Mining;Topic Modeling;Women’s Studies
DO - 10.14431/jaw.2025.12.64.3.197
ER -
Jo, Seong-min, Park, Ha-na, Lee, Hye-Eun and Shin, Dong-hee. (2025). An Analysis of Research Trends in ‘The Journal of Asian Women’ Using Text Mining. 아시아여성연구, 64(3), 197-229.
Jo, Seong-min, Park, Ha-na, Lee, Hye-Eun and Shin, Dong-hee. 2025, "An Analysis of Research Trends in ‘The Journal of Asian Women’ Using Text Mining", 아시아여성연구, vol.64, no.3 pp.197-229. Available from: doi:10.14431/jaw.2025.12.64.3.197
Jo, Seong-min, Park, Ha-na, Lee, Hye-Eun, Shin, Dong-hee "An Analysis of Research Trends in ‘The Journal of Asian Women’ Using Text Mining" 아시아여성연구 64.3 pp.197-229 (2025) : 197.
Jo, Seong-min, Park, Ha-na, Lee, Hye-Eun, Shin, Dong-hee. An Analysis of Research Trends in ‘The Journal of Asian Women’ Using Text Mining. 2025; 64(3), 197-229. Available from: doi:10.14431/jaw.2025.12.64.3.197
Jo, Seong-min, Park, Ha-na, Lee, Hye-Eun and Shin, Dong-hee. "An Analysis of Research Trends in ‘The Journal of Asian Women’ Using Text Mining" 아시아여성연구 64, no.3 (2025) : 197-229.doi: 10.14431/jaw.2025.12.64.3.197
Jo, Seong-min; Park, Ha-na; Lee, Hye-Eun; Shin, Dong-hee. An Analysis of Research Trends in ‘The Journal of Asian Women’ Using Text Mining. 아시아여성연구, 64(3), 197-229. doi: 10.14431/jaw.2025.12.64.3.197
Jo, Seong-min; Park, Ha-na; Lee, Hye-Eun; Shin, Dong-hee. An Analysis of Research Trends in ‘The Journal of Asian Women’ Using Text Mining. 아시아여성연구. 2025; 64(3) 197-229. doi: 10.14431/jaw.2025.12.64.3.197
Jo, Seong-min, Park, Ha-na, Lee, Hye-Eun, Shin, Dong-hee. An Analysis of Research Trends in ‘The Journal of Asian Women’ Using Text Mining. 2025; 64(3), 197-229. Available from: doi:10.14431/jaw.2025.12.64.3.197
Jo, Seong-min, Park, Ha-na, Lee, Hye-Eun and Shin, Dong-hee. "An Analysis of Research Trends in ‘The Journal of Asian Women’ Using Text Mining" 아시아여성연구 64, no.3 (2025) : 197-229.doi: 10.14431/jaw.2025.12.64.3.197