Mining the Demographics of Craigslist Casual Sex Ads to Inform Public Health Policy

机译：挖掘Craigslist休闲性广告的人口统计，以通知公共卫生政策

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Anonymous sexual encounters negotiated via the Internet present many challenges to public health officials addressing outbreaks of sexually transmitted infections. The anonymity and potential geographic scale of encounters weaken traditional tools like contact tracing and partner notification. These developments complicate interventions within the men who have sex with men (MSM) population, which has seen increasing health disparities in HIV and syphilis incidence rates over the last decade. This paper presents text-mining methods for conducting public health surveillance of the anonymous MSM populations using the online classified advertisement website Craig list to negotiate casual sexual encounters. We analyze 2.5 years of Craig list data (134 million ads) and present machine learning and rule-based approaches for efficiently mining race/ethnicity and age information from Craig list text. Using previous work in geographic entity recognition, we link ads with specific locations and generate Craig list MSM summary statistics for race/ethnicity and age cohorts in urban and rural geographic areas. This data is then compared to demographic information from the 2010 U.S. Census to quantify how well it reflects the known, underlying population. We find significant correlations between Craig list and census population statistics, suggesting our approach's utility for surveillance applications.

机译：通过互联网协商的匿名性遭遇为公共卫生官员提供了解决性传播感染疫情的许多挑战。遭遇的匿名和潜在地理规模削弱了与联系跟踪和合作伙伴通知等传统工具。这些发展使与男人（MSM）人口发生性关系的人内的干预措施使其在过去十年中已经看到艾滋病毒和梅毒发病率的增加。本文介绍了使用在线分类广告网站Craig列表进行匿名MSM群体进行公共卫生监测的文本挖掘方法，以协商休闲性遭遇。我们分析了2.5年的CRAIG列表数据（1.34亿广告），并提供基于机器学习和基于规则的方法，以获得来自Craig名单文本的有效挖掘种族/种族和年龄信息。在地理实体识别中使用以前的工作，我们将广告与特定位置链接，并生成CRAIG列表MSM概述城市和农村地理区域的种族/种族和年龄群组的汇总统计数据。然后将该数据与来自2010年美国人口普查的人口统计信息进行比较，以量化它反映了已知的底层人口的程度。我们在CRAIG列表和人口普查人口统计之间发现了显着的相关性，建议我们对监控应用的方法。

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《IEEE International Conference on Healthcare Informatics》|2014年||共10页
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Fries Jason /A/.; Polgreen Philip M.; Segre Alberto M.;
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中图分类生物医学工程;
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Knowledge discovery; Natural language processing; Public healthcare; Supervised learning; Text mining;

机译：知识发现;自然语言处理;公共医疗保健;监督学习;文本挖掘;

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Mining the Demographics of Craigslist Casual Sex Ads to Inform Public Health Policy

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