Stage distinctive communication networks of the online breast cancer community.

In this study, we reveal the distinctive communication network structures and contents of online breast cancer community posts in accordance with different cancer stages. Using data collected from community.breastcancer.org, a major online breast cancer community (28,139 original posts and 663,748 replies), we traced the communication network structures and contents of replies associated with its severity. By combining network and quantitative content analyses, we deciphered the functions and utilities of health-related online communication. We found an inverse relationship between offline epidemiological prevalence and online communication activation. Despite the relatively small percentage of breast cancer patients, it was found that the more severe the condition of breast cancer, the more active online communication was. We further found that as pathological severity advances, communication networks move from informational exchange to emotional support. The capture of online social networks based on the cancer stage can help unpack the distinctive communication patterns found across different cancer severities. Our results provide insights into a possible online communication intervention design tailored to symptom severity.

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 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.

Funding sources and breast cancer research frame.

This study aims to analyze the formation of the frame of breast cancer research. To test our hypothesis that the research frame depends on the funding sources, we collected the abstracts of 48,448 breast cancer research papers from PubMed and applied structural topic modeling, word network analysis, and LASSO logistic regression to the data. In particular, we analyzed the relationship between funding sources and the molecularization of breast cancer knowledge. The results show that government-funded research is likely to have molecular objects or population as the unit of interest, whereas the research not funded by the government is likely to have individual patients as the unit of interest in relation to specific treatments. This phenomenon is attributed to the different interests of government institutions and the private sector. This study improves our understanding of molecularization and medical knowledge production.

News media's framing of health policy and its implications for government communication: A text mining analysis of news coverage on a policy to expand health insurance coverage in South Korea.

On August 9, 2017, South Korea announced a new measure to expand National Health Insurance (NHI) coverage, which was nicknamed "Mooncare." At the early stage of its implementation, the interpretation of a policy by social actors influences its success and the formation of social conflicts around it. This study sought to identify the strategies for interpreting Mooncare in newspapers and government documents and examine the conflicts between them. Therefore, this study used text mining methods that are well-suited to processing large amounts of natural language data. Findings revealed that, while the conservative newspaper The Chosun Ilbo tended to highlight the financial feasibility of Mooncare, the liberal newspaper The Hankyoreh emphasized the change in rationality of government from the previous administration implied by Mooncare. Additionally, medical newspapers tended to adopt the perspective of healthcare providers and to focus on the changes in the medical system that may threaten them. In contrast, general newspapers tended to adopt the perspective of Mooncare's beneficiaries. Finally, government documents were found to focus on simply introducing the benefits of Mooncare, not responding to the framings of various media. This study identified how various social actors interpreted Mooncare. The results suggest that the government should assume a more active role in the meaning making of the policy.