TY -的AU - Chang,安琪拉盟-舒尔茨,彼得约翰AU -焦,温家宝盟——刘,马修Tingchi PY - 2021 DA - 2021/11/23 TI -与肥胖相关的沟通从Mainland China数字中国的新闻,香港和台湾:自动化内容分析乔- JMIR公共卫生Surveill SP - e26660六世- 7 - 11 KW -公共卫生千瓦计算内容KW -数字研究方法千瓦肥胖话语KW -基因失调KW -非传染性疾病AB -背景:世界范围内肥胖人数不断增加，这一事实让人们对媒体向公众提供信息的努力产生了质疑。本研究试图确定主流数字新闻报道肥胖病因和与肥胖负担相关的疾病的方式。目的:本研究的双重目标是获得对肥胖的新闻报道的理解，并通过扩展先入为主的理论来探索数据中的意义。方法:2010年至2019年的10年新闻文本比较了中国大陆、香港和台湾肥胖相关报道的发展及其对其认知的潜在影响。以9家中国主流报纸的数字新闻报道为样本，对其进行了分析。提出了一种自动内容分析工具DiVoMiner。该计算机辅助平台旨在根据单词出现和术语发现的模式组织和过滤大量数据。另一种编程语言Python 3用于探索聚合交互创建的连接和模式。结果:自2016年以来，共有30968条新闻被识别出来并受到越来越多的关注。 The highest intensity of newspaper coverage of obesity communication was observed in Taiwan. Overall, a stronger focus on 2 shared causative attributes of obesity is on stress (n=4483, 33.0%) and tobacco use (n=3148, 23.2%). The burdens of obesity and cardiovascular diseases are implied to be the most, despite the aggregated interaction of edge centrality showing the highest link between the “cancer” and obesity. This study goes beyond traditional journalism studies by extending the framework of computational and customizable web-based text analysis. This could set a norm for researchers and practitioners who work on data projects largely for an innovative attempt. Conclusions: Similar to previous studies, the discourse between the obesity epidemic and personal afflictions is the most emphasized approach. Our study also indicates that the inclination of blaming personal attributes for health afflictions potentially limits social and governmental responsibility for addressing this issue. SN - 2369-2960 UR - https://publichealth.www.mybigtv.com/2021/11/e26660 UR - https://doi.org/10.2196/26660 UR - http://www.ncbi.nlm.nih.gov/pubmed/34817383 DO - 10.2196/26660 ID - info:doi/10.2196/26660 ER -