ArticleInternational neurourology journal2023
Insights Into Korean Public Perspectives on Urology: Online News Data Analytics Through Latent Dirichlet Allocation Topic Modeling.
Article in International neurourology journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 7 citations in OpenAlex.
- Public Perceptions of Male Hormone Levels and Prostate Health: A Text Mining Analysis of South Korean Media and Online Communities.International neurourology journal · 2024Article
- Vasectomy Discussions in South Korea: Central Themes and Public Interest on Question-and-Answer Social Platforms.International neurourology journal · 2024Article
- Public Perceptions of Enuresis: Insights From Online Communities in South Korea and the United States.International neurourology journal · 2024Article
- Transformation in Neurourology.International neurourology journal · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
purposeThe 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.
methodsIn 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.
resultsThe 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.
conclusionBy 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.