Academic Tech Hubs for Human Trafficking

Stanford Human Trafficking Data Lab
Joint Industry-Academic Collection (Traffik Analysis Hub)

Largest Human Trafficking Data in North America:

Other Datasets:

GNN Papers:
  • T-Net: Weakly Supervised Graph Learning for Combatting Human Trafficking
  • IMBWatch: A Spatio-Temporal Graph Neural Network Framework
  • Investigating Links between Illicit Massage Businesses through NLP and Graph Machine Learning
  • Hybrid Transformer-GNN Frameworks for Digital Platform Detection
  • Temporal-Attention GNNs for Supply Chain Modern Slavery Identification
  • Analyzing Human Trafficking Networks Using Graph-Based Multi-Modal Fusion
  • Inductive Graph-Sage (GraphSAGE) for Malicious Intent Detection
  • Graph Autoencoders (GAEs) for Social Media Profiling & Bot Detection
  • Multi-Modal Fusion Heterogeneous GNNs (Social Media Recruitment)
  • The Trafficker's Pitch: Detecting Deceptive Recruitment in Online Job Boards
  • Multi-Modal Behavior & Network Analysis for Combatting Child Grooming
  • Filter-then-Verify: Inductive GNN and BERT Co-Attention Framework
  • Relational Graph Convolutional Networks (R-GCN) for Fake "Agency" Detection
  • Social Botnet Detection via Graph Autoencoders (GAEs)
  • Hypergraph Neural Networks (HGNNs) for Coded Multi-Platform Evasion
  • Algorithmic Exploitation in Social Media Human Trafficking and Strategies for Regulation
  • Human Trafficking in Social Networks: A Review of Machine Learning Techniques
  • Cyber Slavery: AI-Enabled Detection and National Countermeasures
  • Online Chat Child Grooming and Exploitation Detection Using Phase-Aware Graph Neural Networks
  • Detecting Cyberbullying and Coercive Intimidation on Social Networks via Multi-View Graph Neural Networks
  • HOT-GNN: A Heterophily Outlier Temporal-Aware Graph Neural Network for Camouflaged Fraud and Coercion
  • Hierarchical Emotion-Aware Graph Attention Networks for Online Grooming Detection
  • Modeling Sociotechnical Dynamics and Coercive Trust Exploitation via Heterogeneous Graph Neural Networks
  • Multi-Modal Affective Fusion over Graph Autoencoders for Detecting Financial Sextortion
  • Temporal Graph Neural Networks with Affective Contagion for Insider Threat and Coercive Control
  • Money Laundering Detection Using Graph Neural Networks Enhanced with Autoencoder Components
  • Intelligent Anti-Money Laundering Transaction Pattern Recognition System Based on Graph Neural Networks
  • Cyber Violence Text Classification Model Based on Graph Convolutional Networks and Syntactic Parsing
  • SosNet: A Graph Convolutional Network Approach to Fine-Grained Cyberbullying Detection