ArticleScientific reports2022
Online information analysis on pancreatic cancer in Korea using structural topic model.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The trial behind it
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Who cites it
5 citing papers in PubMed.
- User-Reported Issues With Mental Health Apps: Machine-Assisted Topic Analysis of Social Media Posts.JMIR mHealth and uHealth · 2026Article
- Detecting Conversation Topics in Recruitment Calls of African American Participants to the All of Us Research Program Using Machine Learning: Model Development and Validation Study.JMIR formative research · 2025Article
- Harnessing Social Media Data to Understand Information Needs About Kidney Diseases and Emotional Experiences With Disease Management: Topic and Sentiment Analysis.Journal of medical Internet research · 2025Article
- Assessing GPT-4's Performance in Delivering Medical Advice: Comparative Analysis With Human Experts.JMIR medical education · 2024Article
- [Structural Topic Modeling Analysis of Patient Safety Interest among Health Consumers in Social Media].Journal of Korean Academy of Nursing · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Inappropriate information on a deadly and rare disease can make people vulnerable to problematic decisions, leading to irreversible bad outcomes. This study explored online information exchanges on pancreatic cancer. We collected 35,596 questions and 83,888 answers related to pancreatic cancer from January 1, 2003 to May 31, 2020, from Naver, the most popular Korean web portal. We also collected 8495 news articles related to pancreatic cancer during the same period. The study methods employed were structural topic modeling, keyword frequency analysis, and qualitative coding of medical professionals. The number of questions and news articles increased over time. In Naver's questions, topics on symptoms and diagnostic tests regarding pancreatic cancer increased in proportion. The news topics on new technologies related to pancreatic cancer from various companies increased as well. The use of words related to back pain-which is not an important early symptom in pancreatic cancer-and biomarker tests using blood increased over time in Naver's questions. Based on 100 question samples related to symptoms and diagnostic tests and an analysis of the threaded answers' appropriateness, there was considerable misinformation and commercialized information in both categories.
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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.