This tool is a part of the paper "Inductive and Transductive Link Prediction for Criminal Network Analysis," published in the Journal of Computational Science in 2023. It implements an analyzer and visualizer specialized for criminal (social) network analysis, including community detection, social influence analysis, and link prediction.

Data visualization project that shows info about criminal acts produced on the road network in Catalonia, Spain.

criminal-network-mapper is a data-driven system that maps and visualizes criminal networks, identifies key actors (kingpins, facilitators, brokers), and simulates potential threat pathways through advanced network analysis.

Analysis of a 2-year criminal network with 101 players, disturbed by police actions. Utilizes graph visualization and centrality measures to identify key figures and trends. Highlights the effectiveness of degree centrality in revealing vital network players and their evolving roles.

B.Tech Final Year Project

Project analyzing criminal activity networks using data from various sources to understand patterns and connections.

No description available

An AI-powered Smart Policing dashboard utilizing Spatio-Temporal Graph Attention Networks (ST-GAT) to visualize criminal patterns. Engineered with a focus on intuitive data visualization and user-centric design for law enforcement.

Black Vein Oracle revolutionizes criminal investigation with real-time network tracking. Agents log incidents while Headquarters receives live alerts when threats spike dangerously high. The system visualizes complex criminal connections through animated maps and interactive timeline sliders.

This tool helps defense analysts create visualizations of their multi-dimensional analyses (a research technique used for identifying and analyzing the pieces of amorphous criminal networks by first identifying the processes they must undertake, then identifying the types of people they would need to do those tasks, then working from whatever information they already have about the network to quickly narrow down their hypotheses about who could be involved at the other steps). The visualizer allows analysts to type in a list of people and processes, using indentation to indicate which tasks are prerequisites of which and the hierarchy of the people involved. Then it draws a picture. It automatically detects the difference between processes and people, and it labels them differently with different colors and shapes. Uses the Graphviz gem for the drawing.