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Protecting Children Online: Using Research-Based Algorithms to Prioritize Law Enforcement Internet Investigations, Technical Report

NCJ Number
250154
Author(s)
R. Gregg Dwyer; Michael Seto; Dana DeHart; Elizabeth Letourneau; Tracy McKee; Robert Moran
Date Published
May 2016
Length
54 pages
Annotation

This project developed empirically based recommendations that assist law enforcement task forces on Internet Crimes Against Children to prioritize cases that involve the production of child pornography rather than its possession/distribution; cases that involve online efforts to lure children into sexual contact rather than those restricted to sexual chat or the exchange of pornographic images; and cases that involve offenders who have committed contact sexual offenses against children over cases of offenders with no known history of such contact.

Abstract

Although all instances of Internet offending against minors require intervention, the large number of cases and limited law enforcement resources require the prioritization of cases. Using data on offender characteristics, crime characteristics, and online behavior from 20 Internet Crimes Against Children task forces from across the United States, the current project identified variables that can be readily available to law enforcement officers at the field-investigation stage for the purpose of distinguishing and giving priority to cases that involve producers of child pornography, contact-driven sexual solicitations of children, and Internet offenders who have also committed contact sexual offenses. It is important that these high-priority cases be identified early in case development so resources may be appropriately allocated as early as possible in the investigation. Identified variables important to the prioritization of cases pertain to offender motivations, solicitation offender types, contact offending history, the risk of sexual recidivism, and the characteristics of online activity. Inferential statistical analysis of data was conducted to identify significant associations among offender, victim, and crime details in order to identify types of offenders. Content analysis of sexual chat text was conducted to identify patterns associated with higher priority cases. The study also exposed the difficulty in conducting a retrospective file-based study using data not originally collected for research. 5 tables and 34 references