Arthur J. Villasanta – Fourth Estate Contributor
West Lafayette, IN, United States (4E) – An algorithm developed by faculty at the Purdue Polytechnic Institute in Indiana will help law enforcement agencies filter out and focus on sex offenders most likely to set up face-to-face meetings with child victims.
The “Chat Analysis Triage Tool” (CATT) was recently presented at the International Association of Law Enforcement Intelligence Analysts Conference in Anaheim, California by principal investigator Kathryn Seigfried-Spellar, assistant professor of computer and information technology.
CATT allows police officers to work through the massive volume of solicitations and use algorithms to examine the word usage and conversation patterns by a suspect. Seigfried-Spellar said data was taken from online conversations provided voluntarily by law enforcement around the USA. The project started as a result of a partnership with the Ventura County Sheriff’s Department in California.
Initial plans are to turn CATT over to several law enforcement departments for a test run. Seigfried-Spellar said CATT could be handling data from active cases as early as the end of the year.
She noted that law enforcement officers are overwhelmed by the sheer number of cases involving the sexual solicitation of minors. Some of these perverts are interested in sexual fantasy chats while others attempt to persuade an underage victim into a face-to-face meeting.
“We went through and tried to identify language-based differences and factors like self-disclosure,” she said. “If we can identify language differences, then the tool can identify these differences in the chats in order to give a risk assessment and a probability that this person is going to attempt face-to-face contact with the victim. That way, officers can begin to prioritize which cases they want to put resources toward to investigate more quickly.”
Self-disclosure is a tactic in which the suspect tries to develop trust by sharing a personal story, which is usually negative, such as parental abuse. Other standout characteristics of sexual predators grooming victims for a face-to-face meeting is that the chats will often go on for weeks or even months until a meeting is achieved. Those involved in sexual fantasy chatting move on from one youth to another quickly.
Seigfried-Spellar said the research discovered tactics like self-disclosure is used early in a predator’s talks with a potential victim. “Meaning that we could potentially stop a sex offense from occurring because if law enforcement is notified of a suspicious chat quickly enough, CATT can analyze and offer the probability of a face-to-face,” she said. “We could potentially prevent a child from being sexually assaulted.”
Seigfried-Spellar worked in developing CATT with two co-principal investigators, associate professor Julia Taylor Rayz, who specializes in machine learning and natural language processing, and Marcus Rogers, computer and information technology department head, who has an extensive background in digital forensics tool development.
CATT algorithms examine only the conversation factors and do not take the sex of either suspect or victim into consideration, at this time.
The project began with initial research done by Seigfried-Spellar and former Purdue professor Ming Ming Chiu. The exploratory study examined more than 4,300 messages in 107 online chat sessions involving arrested sex offenders, identifying different trends in word usage and self-disclosure by fantasy and contact sex offenders using statistical discourse analysis. The trends determined through this research formed the basis for CATT.
The research, “Detecting Contact vs. Fantasy Online Sexual Offenders in Chats with Minors: Statistical Discourse Analysis of Self-Disclosure and Emotion Words,” has been accepted and will be published in the journal “Child Abuse and Neglect.”
Article – All Rights Reserved.
Provided by FeedSyndicate