Automated News Scraping and AI-Powered Analysis for Municipal Crime Mapping

Pedro Arthur P. S. Ortiz, Leandro O. Freitas

2025

Abstract

This paper presents an innovative approach to urban crime mapping through automated web scraping and data analysis techniques, addressing the challenge of limited crime data availability in smaller municipalities. Focusing on Santa Maria, Brazil, we develop a methodology to extract, process, and visualize crime-related information from local news sources. Our approach combines web scraping using Selenium, natural language processing with the Claude API, and data visualization techniques to create a comprehensive crime dataset. Through implementation, we present heat maps of crime hotspots, temporal analysis of crime patterns, and statistical correlations between crime-related factors. The research examines hourly, daily, and seasonal crime patterns, providing insights for law enforcement resource allocation. We discuss challenges and ethical considerations of using web-scraped data, including privacy concerns, reporting bias, and verification challenges. While acknowledging limitations such as data bias and accuracy concerns, this research provides a foundation for data-driven urban crime prevention strategies. The methodology offers a scalable framework that could be implemented across various urban environments, contributing to more effective crime prevention and public safety strategies.

Paper Citation

in Harvard Style

Ortiz P. and Freitas L. (2025). Automated News Scraping and AI-Powered Analysis for Municipal Crime Mapping. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 742-749. DOI: 10.5220/0013178200003890

in Bibtex Style

@conference{icaart25,
author={Pedro Ortiz and Leandro Freitas},
title={Automated News Scraping and AI-Powered Analysis for Municipal Crime Mapping},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2025},
pages={742-749},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013178200003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Automated News Scraping and AI-Powered Analysis for Municipal Crime Mapping
SN - 978-989-758-737-5
AU - Ortiz P.
AU - Freitas L.
PY - 2025
SP - 742
EP - 749
DO - 10.5220/0013178200003890
PB - SciTePress