Analysis of Women's Health Online News Articles Using Topic Modeling
10.24171/j.phrp.2019.10.3.07
- Author:
Kyoung Won CHO
1
;
Shine Young KIM
;
Young Woon WOO
Author Information
1. Department of Healthcare Administration, Kosin University, Busan, Korea.
- Publication Type:Newspaper Article
- Keywords:
data mining;
newspaper article;
women's health
- MeSH:
Data Mining;
Delivery of Health Care;
Women's Health
- From:
Osong Public Health and Research Perspectives
2019;10(3):158-169
- CountryRepublic of Korea
- Language:English
-
Abstract:
OBJECTIVES: This research aimed to understand the popularity of topics in the field of women's health through analysis of online news articles which were chronologically classified and examined to determine how women's health and diseases had changed over time. METHODS: Women's health and disease news articles were collated from a popular news website between 1993 to 2015 and preprocessed using gynecological medical terminology, Korean words and nouns (excluding general nouns not related to women's healthcare topics). The resultant articles (N = 7,710) were analyzed using the Latent Dirichlet Allocation algorithm and major topics were extracted. Topic trends were analyzed by year and period for women's health. RESULTS: It was observed that most of the women's health articles were focused on “Healthcare”, and 9 other topics were identified that represented a relatively small proportion in 1993–2000. In 2001–2005, most of the articles were focused on “Medical Services” and “Dietary Supplements” with some specific topics that peaked people's interest, as compared to those focused on “Healthcare” in the 1990s. It was also observed that differences in the proportion of each topic was small after 2011. CONCLUSION: Changes in topics related to women's disease were not clearly distinguished in the 1990s but this changed from 2001where articles related to “women disease” appeared as articles on the topics of various diseases.
