@文章{信息:doi/10.2196/11073，作者="Biancovilli, Priscila和Jurberg, Claudia"，标题="如何优化Facebook上关于癌症的健康信息:混合方法研究"，期刊="JMIR癌症"，年="2018"，月=" 12月"，日="18"，卷="4"，数="2"，页="e11073"，关键词="癌症;内容分析;Facebook;健康;背景:世界范围内癌症的发病率正在上升，预期寿命的延长是主要原因之一。然而，30%到50%的癌症病例是可以预防的，早期发现有助于更好的预后。这使得卫生传播战略至关重要。Facebook是2017年和2018年世界上使用最多的社交网站，可以成为传播关于健康促进、预防和早期发现的强有力信息的有用工具。目标:我们的目标是:(1)提供优化Facebook上关于癌症的健康信息的方法，重点关注风险因素、预防、治疗、早期诊断和治愈等主题，以及(2)调查这些信息的哪些方面能产生更大的参与度。方法:为了验证是什么在Facebook上吸引了更多与癌症相关的话题，我们分析了16个以癌症为主题的巴西页面。 We performed a manual analysis of texts, content, and engagement rates. Finally, we developed a software program to operationalize the analysis of Facebook posts. The tool we devised aims to automate the analysis of any Facebook page with cancer as the main theme. Results: We analyzed 712 posts over a 1-month period. We divided the posts into the following 8 categories: ``Testimonies or real-life stories,'' ``Solidarity,'' ``Anniversaries,'' ``Science and health,'' ``Events,'' ``Institutional,'' ``Risk factors,'' and ``Beauty.'' The pages were also organized into groups according to the type of profile to which they belonged (ie, hospitals or foundations, informative, nongovernmental organizations, and personal pages).The results showed that the categories generating greater engagement in Brazil were not those with the highest percentage of cancer-related content. For instance, in the ``Informative'' group the ``Testimonies or real-life stories'' category generated an engagement of 79.5{\%}. However, only 9.5{\%} (25/261) of the content within the relevant time period dealt with such topics. Another example concerns the category ``Science and health.'' Despite being the one with the highest number of posts (129/261, 49.4{\%}), it scored 5th in terms of engagement. This investigation served as the basis for the development of a tool designed to automate the analysis of Facebook pages. The list of categories and keywords generated by this analysis was employed to feed the system, which was then able to categorize posts appearing on a Facebook page. We tested the system on 163 posts and only 34 were classified incorrectly, which amounts to a 20.8{\%} error rate (79.2{\%} accuracy). Conclusions: The analysis we conducted by categorizing posts and calculating engagement rates shows that the potential of Facebook pages is often underutilized. This occurs because the categories that generate the greatest engagement are often not those most frequently used. The software developed in this research may help administrators of cancer-related pages analyze their posts more easily and increase public interest as a result. ", issn="2369-1999", doi="10.2196/11073", url="http://cancer.www.mybigtv.com/2018/2/e11073/", url="https://doi.org/10.2196/11073", url="http://www.ncbi.nlm.nih.gov/pubmed/30563821" }