Reconstructing and Analyzing the Transnational Human Trafficking Network

被引:2
作者
Goist, Mitchell [1 ]
Chen, Ted Hsuan Yun [1 ]
Boylan, Christopher [2 ]
机构
[1] Penn State Univ, Dept Polit Sci, University Pk, PA 16802 USA
[2] Ver Maplecroft, Dublin, Ireland
来源
PROCEEDINGS OF THE 2019 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM 2019) | 2019年
关键词
D O I
10.1145/3341161.3342879
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Human trafficking is a global problem which impacts a countless number of individuals every year. In this project, we demonstrate how machine learning techniques and qualitative reports can be used to generate new valuable quantitative information on human trafficking. Our approach generates original data, which we release publicly, on the directed trafficking relationship between countries that can be used to reconstruct the global transnational human trafficking network. Using this new data and statistical network analysis, we identify the most influential countries in the network and analyze how different factors and network structures influence transnational trafficking. Most importantly, our methods and data can be employed by policymakers, non-governmental organizations, and researchers to help combat the problem of human trafficking.
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收藏
页码:493 / 500
页数:8
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