@文章{信息:doi/10.2196/18767，作者=“Lee Jooyun and Park, hyun - ae and Park, Seul Ki and Song Tae-Min”，标题=“利用社交媒体数据了解癌症相关消费者的信息需求和情绪:基于本体的数据分析研究”，期刊=“J Med Internet Res”，年=“2020”，月=“12”，日=“7”，卷=“22”，数=“12”，页=“e18767”，关键词=“社交媒体;本体;癌症;卫生信息需求;癌症信息;背景:分析社交媒体上的帖子可以有效地调查疾病管理的健康信息需求，并识别人们与疾病相关的情绪状态。对社交媒体数据进行语义分析需要本体。目的:本研究旨在开发包含消费者术语的癌症本体，并分析社交媒体数据，以识别与癌症相关的健康信息需求和情绪。方法:使用2014年1月1日至2017年6月30日期间在韩国在线社区和博客中使用爬虫收集的社交媒体数据开发癌症本体。统计包含本体论概念的帖子的相对频率，并按癌症类型进行比较。 Results: The ontology had 9 superclasses, 213 class concepts, and 4061 synonyms. Ontology-driven natural language processing was performed on the text from 754,744 cancer-related posts. Colon, breast, stomach, cervical, lung, liver, pancreatic, and prostate cancer; brain tumors; and leukemia appeared most in these posts. At the superclass level, risk factor was the most frequent, followed by emotions, symptoms, treatments, and dealing with cancer. Conclusions: Information needs and emotions differed according to cancer type. The observations of this study could be used to provide tailored information to consumers according to cancer type and care process. Attention should be paid to provision of cancer-related information to not only patients but also their families and the general public seeking information on cancer. ", issn="1438-8871", doi="10.2196/18767", url="//www.mybigtv.com/2020/12/e18767/", url="https://doi.org/10.2196/18767", url="http://www.ncbi.nlm.nih.gov/pubmed/33284127" }