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Online information analysis on pancreatic cancer in Korea using structural topic model

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...

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Autores principales: Jo, Wonkwang, Kim, Yeol, Seo, Minji, Lee, Nayoung, Park, Junli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9218710/
https://www.ncbi.nlm.nih.gov/pubmed/35739151
http://dx.doi.org/10.1038/s41598-022-14506-1
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author Jo, Wonkwang
Kim, Yeol
Seo, Minji
Lee, Nayoung
Park, Junli
author_facet Jo, Wonkwang
Kim, Yeol
Seo, Minji
Lee, Nayoung
Park, Junli
author_sort Jo, Wonkwang
collection PubMed
description 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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spelling pubmed-92187102022-06-23 Online information analysis on pancreatic cancer in Korea using structural topic model Jo, Wonkwang Kim, Yeol Seo, Minji Lee, Nayoung Park, Junli Sci Rep Article 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. Nature Publishing Group UK 2022-06-23 /pmc/articles/PMC9218710/ /pubmed/35739151 http://dx.doi.org/10.1038/s41598-022-14506-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Jo, Wonkwang
Kim, Yeol
Seo, Minji
Lee, Nayoung
Park, Junli
Online information analysis on pancreatic cancer in Korea using structural topic model
title Online information analysis on pancreatic cancer in Korea using structural topic model
title_full Online information analysis on pancreatic cancer in Korea using structural topic model
title_fullStr Online information analysis on pancreatic cancer in Korea using structural topic model
title_full_unstemmed Online information analysis on pancreatic cancer in Korea using structural topic model
title_short Online information analysis on pancreatic cancer in Korea using structural topic model
title_sort online information analysis on pancreatic cancer in korea using structural topic model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9218710/
https://www.ncbi.nlm.nih.gov/pubmed/35739151
http://dx.doi.org/10.1038/s41598-022-14506-1
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