An End-to-End Framework for Dynamic Crime Profiling of Places

TL;DR

This paper presents an automated, real-time framework that extracts and integrates online news crime data to dynamically profile and visualize crime-prone areas, aiding safety assessments.

Contribution

It introduces an end-to-end system for crime profiling that automates data collection, analysis, and visualization from unstructured online news sources.

Findings

Successfully extracted crime data from over 345,000 news articles.

Generated accurate crime heat maps matching manual ratings.

Demonstrated real-time, dynamic crime profiling capabilities.

Abstract

Much effort is being made to ensure the safety of people. One of the main requirements of travellers and city administrators is to have knowledge of places that are more prone to criminal activities. To rate a place as a potential crime location, it needs the past crime history at that location. Such data is not easily available in the public domain, however, it floats around on the Internet in the form of newspaper and social media posts, in an unstructured manner though. Consequently, a large number of works are reported on extracting crime information from news articles, providing piecemeal solutions to the problem. This chapter complements these works by building an end-to-end framework for crime profiling of any given location/area. It customizes individual components of the framework and provides a Spatio-temporal integration of crime information. It develops an automated framework that crawls online news articles, analyzes them, and extracts relevant information to create a crime knowledge base that gets dynamically updated in real-time. The crime density can be easily visualized in the form of a heat map which is generated by the knowledge base. As a case study, it investigates 345448 news articles published by 6 daily English newspapers collected for approximately two years. Experimental results show that the crime profiling matches with the ratings calculated manually by various organizations.