Int Neurourol J.  2023 Nov;27(Suppl 2):S91-98. 10.5213/inj.2346288.144.

Insights Into Korean Public Perspectives on Urology: Online News Data Analytics Through Latent Dirichlet Allocation Topic Modeling

• Oh YW
• Kim J

• KMID: 2548213
• DOI: http://doi.org/10.5213/inj.2346288.144

Abstract

Purpose
The objective of the study was to explore how urology-related news, one of the medical specialties profoundly linked to human health and life, is communicated to the public through media outlets that serves as primary sources of medical information for the public.
Methods
In this study, articles were retrieved using the keyword ‘Urology’ from the Bigkinds spanning from January 1, 1990 to August 17, 2023. The Beautifulsoup library in Python was utilized for parsing the text to collect both titles and bodies of the articles. The gathered data was then analyzed using the latent Dirichlet allocation (LDA) algorithm from the scikit-learn library. Additionally, tools such as Wordcloud and Networkx were employed to visualize the relationships and patterns within the data.
Results
The keyword analysis led to the identification of various themes in the articles, with a clear distinction between those providing medical information and those promoting healthcare services, technologies, and products. Notably, the content frequently intertwined informational aspects with promotional ones. Articles on men’s health and pet diseases, for example, often combined educational material with product or procedure promotions. This overlap highlights the complexity of categorizing media content into distinct themes. Furthermore, the coverage of health insurance and treatment methods including recent advancements like robotic surgery reflected the evolving nature of healthcare discussions to emphasize the interplay between policy changes, medical advancements, and media portrayal.
Conclusions
By identifying 10 distinct topics mentioned in the news, the analysis determined which topics are common in urology-related news coverage. The findings revealed a substantial volume of medical information on urology in the media with a wide range of topics including treatment and prevention of urologic conditions, insurance information, new treatments, and news stories promoting new products or hospitals.

Keyword

Urology; Online news; Public awareness; Data mining; Latent Dirichlet allocation