Guarding the Guardians: Automated Analysis of Online Child Sexual Abuse

TL;DR

This paper introduces an automated tool for analyzing online child sexual abuse reports, reducing exposure to harmful content and aiding law enforcement in understanding crime patterns to develop targeted interventions.

Contribution

The paper presents a novel automated analysis system for abuse reports, including a new annotation approach that enhances understanding of crime dynamics.

Findings

Significantly reduces analyst exposure to harmful content

Categorizes reports on Subject, Criminality, and Damage

Enables in-depth pattern analysis for law enforcement

Abstract

Online violence against children has increased globally recently, demanding urgent attention. Competent authorities manually analyze abuse complaints to comprehend crime dynamics and identify patterns. However, the manual analysis of these complaints presents a challenge because it exposes analysts to harmful content during the review process. Given these challenges, we present a novel solution, an automated tool designed to analyze children's sexual abuse reports comprehensively. By automating the analysis process, our tool significantly reduces the risk of exposure to harmful content by categorizing the reports on three dimensions: Subject, Degree of Criminality, and Damage. Furthermore, leveraging our multidisciplinary team's expertise, we introduce a novel approach to annotate the collected data, enabling a more in-depth analysis of the reports. This approach improves the comprehension of fundamental patterns and trends, enabling law enforcement agencies and policymakers to create focused strategies in the fight against children's violence.