Methods of using real-time social media technologies for detection and remote monitoring of HIV outcomes.

Methods of using real-time social media technologies for detection and remote monitoring of HIV outcomes.
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DOI:
10.1016/j.ypmed.2014.01.024
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发表时间:
2014-06
影响因子:
5.1
通讯作者:
Lewis, Bryan
Lewis, Bryan
中科院分区:
医学2区
文献类型:
--
作者:
Young, Sean D.;Rivers, Caitlin;Lewis, Bryan

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最近可用的“大数据”可用于研究是否以及如何在实时社交网站上传播性风险行为,以及数据如何为艾滋病毒预防和检测提供信息。这项研究旨在建立使用实时社交网络数据进行艾滋病毒预防的方法,评估1)是否可以从社交网络数据中提取关于艾滋病毒风险行为的地理定位对话,2)这些对话的流行率和内容,以及3)使用艾滋病毒风险相关的实时社交媒体对话作为检测艾滋病毒结果的方法的可行性。2012年,在线收集了推文(N = 553,186,061),并对其进行了过滤,以包括那些与艾滋病毒风险相关的关键词(例如,性行为和吸毒)。数据与艾滋病毒/艾滋病/SVU关于艾滋病毒病例的数据合并。负二项回归评估了艾滋病毒风险推文与县流行率之间的关系,控制了社会经济地位的措施。提取了9 800多条有地理位置的推文,并用于制作显示艾滋病毒相关推文地理位置的地图。艾滋病毒相关推文与艾滋病毒病例之间存在显著的正相关关系(p <0.01)。结果表明,使用社交网络数据作为评估和检测艾滋病毒风险行为和结果的方法是可行的。
Recent availability of “big data” might be used to study whether and how sexual risk behaviors are communicated on real-time social networking sites and how data might inform HIV prevention and detection. This study seeks to establish methods of using real-time social networking data for HIV prevention by assessing 1) whether geolocated conversations about HIV risk behaviors can be extracted from social networking data, 2) the prevalence and content of these conversations, and 3) the feasibility of using HIV risk-related real-time social media conversations as a method to detect HIV outcomes. In 2012, tweets (N = 553,186,061) were collected online and filtered to include those with HIV risk-related keywords (e.g., sexual behaviors and drug use). Data were merged with AIDSVU data on HIV cases. Negative binomial regressions assessed the relationship between HIV risk tweeting and prevalence by county, controlling for socioeconomic status measures. Over 9,800 geolocated tweets were extracted and used to create a map displaying the geographical location of HIV-related tweets. There was a significant positive relationship (p < .01) between HIV-related tweets and HIV cases. Results suggest the feasibility of using social networking data as a method for evaluating and detecting HIV risk behaviors and outcomes.
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