KMID : 1120220190100030158
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Osong Public Health and Research Perspectives 2019 Volume.10 No. 3 p.158 ~ p.169
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Analysis of Women¡¯s Health Online News Articles Using Topic Modeling
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Cho Kyoung-Won
Kim Shine-Young Woo Young-Woon
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Abstract
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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.
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KEYWORD
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data mining, newspaper article, women¡¯s health
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