D-ISN/RAPID: Data Collection for Human Trafficking Recruitment and Responses in Forced Migration

这项快速反应研究（RAPID）赠款将支持收集有关在线贩运招募和应对活动的时间敏感的定性和定量数据，这些活动针对因乌克兰冲突而被迫流离失所的弱势群体。 传闻证据表明，人为和自然灾害造成并加剧了脆弱性，导致人口贩运网络的剥削。 自2022年2月下旬以来，已有800多万乌克兰人在境外寻求庇护，其中90%是妇女和儿童;另有1000万人在国内流离失所。 失去稳定的住房、就业和社会支持网络都是人口贩运的主要风险因素。 由于入侵，出现了无数针对住房和就业机会的网站和社交媒体聊天组。虽然这类在线论坛使数百万人获得了急需的信息，但它们也为贩运人口的招募提供了肥沃的土壤。 该项目有三个主要目标，即（1）收集关于在何处以及如何招募人员的数据;（2）记录潜在贩运目标正在寻求哪些服务/资源;以及（3）访问和收集关于国际和地方组织使用热线和庇护所的不断发展的干预措施的数据。调查人员将利用其建立的关系收集以下定量和定性数据：提供住房和工作信息的公共公告网站、社交媒体网站和国际援助组织。 该项目将部署网络抓取工具，从网上来源收集数据，并将与非政府援助组织进行结构化访谈。 生成的数据集将在伍斯特理工学院的计算设施中收集，策划和存档，并与更广泛的研究社区广泛共享。 这个奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

This Rapid Response Research (RAPID) grant will support collection of time-sensitive qualitative and quantitative data regarding online trafficking recruitment and response activity for a vulnerable population subject to involuntary displacement because of the conflict in Ukraine. Anecdotal evidence suggests that man-made and natural disasters create and exacerbate vulnerabilities that lead to exploitation by human trafficking networks. Since late February 2022, over 8 million Ukrainians have sought refuge outside the country's borders, 90% of whom are women and children; an additional 10 million are internally displaced. Loss of stable housing, employment, and social support networks are all key risk factors for human trafficking. As a result of the invasion, a myriad of websites and social media chat groups have emerged targeting housing and employment opportunities. While such online forums connect millions to much needed information, they also pose fertile ground for trafficking recruitment. This project has three main aims, namely (1) to collect data on where and how people are being recruited; (2) to document which services/resources potential trafficking targets are seeking; and (3) to interview and collect data on evolving interventions used by international and local organizations operating hotlines and shelters.The investigators will use their established connections to collect the following quantitative and qualitative data: public bulletin websites that offer information on housing and job information, social media websites, and international assistance organizations. The project will deploy web scraping tools to collect data from the online sources and will conduct structured interviews with non-governmental assistance organizations. The generated datasets will be collected, curated, and archived at computing facilities at Worcester Polytechnic Institute and shared widely with the broader research community. The project will involve graduate students and provide them exposure to interdisciplinary research.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.