Semi-supervised learning for detecting human trafficking

Hamidreza Alvari,J. E. Kelly Snyder,Paulo Shakarian

doi:10.1186/s13388-017-0029-8

Abstract

Human trafficking is one of the most atrocious crimes and among the challenging problems facing law enforcement which demands attention of global magnitude. In this study, we leverage textual data from the website “Backpage”—used for classified advertisement—to discern potential patterns of human trafficking activities which manifest online and identify advertisements of high interest to law enforcement. Due to the lack of ground truth, we rely on a human analyst from law enforcement, for hand-labeling a small portion of the crawled data. We extend the existing Laplacian SVM and present S^3VM-R, by adding a regularization term to exploit exogenous information embedded in our feature space in favor of the task at hand. We train the proposed method using labeled and unlabeled data and evaluate it on a fraction of the unlabeled data, herein referred to as unseen data, with our expert’s further verification. Results from comparisons between our method and other semi-supervised and supervised approaches on the labeled data demonstrate that our learner is effective in identifying advertisements of high interest to law enforcement.

Highlights

According to the United Nation [1], human trafficking is defined as the modern slavery or the trade of humans mostly for the purpose of sexual exploitation and forced labor, via different improper ways including force, fraud and deception
In this article, expanding on our previous work [15], we use the data crawled from the adult entertainment section of the website Backpage.com and extend the existing Laplacian support vector machines classifiers (SVM) framework [14] to detect escort advertisements of high interest to law enforcement
Readily available online data from escort advertisements could be leveraged in favor of fight against human trafficking

Summary

Introduction

According to the United Nation [1], human trafficking is defined as the modern slavery or the trade of humans mostly for the purpose of sexual exploitation and forced labor, via different improper ways including force, fraud and deception. In this article, expanding on our previous work [15], we use the data crawled from the adult entertainment section of the website Backpage.com and extend the existing Laplacian SVM framework [14] to detect escort advertisements of high interest to law enforcement.

Results

Conclusion