%0期刊文章%@ 2369-2960 %I JMIR出版物%V 4% 卡塔尔世界杯8强波胆分析N 4% P e10834 %T描述关于宾夕法尼亚州常见健康状况的推文数量和内容:回顾性分析%A塔夫茨，Christopher %A Polsky,Daniel %A Volpp,Kevin G %A Groeneveld,Peter W %A Ungar,Lyle %A Merchant,Raina M %A Pelullo,Arthur P %+数字健康中心，宾夕法尼亚医学院，3400市民中心大道，费城，美国，1 215 615 0890,Raina.Merchant@uphs.upenn.edu %K推特消息%K疾病%K患病率%K公共卫生监测%K社交媒体%D 2018 %7 06.12.2018 %9原始论文%J JMIR公共卫生监测%G英文%X背景:推文可以提供关于健康和医疗诊断的广泛实时观点，可以为地理区域的疾病监测提供信息。然而，人们对个人发布了多少常见健康状况或他们发布了什么内容却知之甚少。目的:我们试图收集和分析来自一个州的关于高流行健康状况的推文，并描述推文的数量和内容。方法:我们收集了2012-2015年来自宾夕法尼亚州的408,296,620条推文，并将14种常见疾病的患病率与推特上提到疾病的频率进行了比较。我们识别并纠正了由于疾病术语特异性方差引起的偏差，并使用差分语言分析的机器学习方法来确定与每种疾病最相关的内容(单词和主题)。结果:常见疾病术语包含在226,802条推文中(疾病术语校正后的174,381条推文)。关于乳腺癌的帖子(39156 / 174381条，22.45%;306,127/12,702,379患病率，2.41%)和糖尿病(40,217/174,381条信息，23.06%; 2,189,890/12,702,379 prevalence, 17.24%) were overrepresented on Twitter relative to disease prevalence, whereas hypertension (17,245/174,381 messages, 9.89%; 4,614,776/12,702,379 prevalence, 36.33%), chronic obstructive pulmonary disease (1648/174,381 messages, 0.95%; 1,083,627/12,702,379 prevalence, 8.53%), and heart disease (13,669/174,381 messages, 7.84%; 2,461,721/12,702,379 prevalence, 19.38%) were underrepresented. The content of messages also varied by disease. Personal experience messages accounted for 12.88% (578/4487) of prostate cancer tweets and 24.17% (4046/16,742) of asthma tweets. Awareness-themed tweets were more often about breast cancer (9139/39,156 messages, 23.34%) than asthma (1040/16,742 messages, 6.21%). Tweets about risk factors were more often about heart disease (1375/13,669 messages, 10.06%) than lymphoma (105/4927 messages, 2.13%). Conclusions: Twitter provides a window into the Web-based visibility of diseases and how the volume of Web-based content about diseases varies by condition. Further, the potential value in tweets is in the rich content they provide about individuals’ perspectives about diseases (eg, personal experiences, awareness, and risk factors) that are not otherwise easily captured through traditional surveys or administrative data. %M 30522989 %R 10.2196/10834 %U http://publichealth.www.mybigtv.com/2018/4/e10834/ %U https://doi.org/10.2196/10834 %U http://www.ncbi.nlm.nih.gov/pubmed/30522989