straycat19 Posted April 20, 2018 Share Posted April 20, 2018 A group of professors at Purdue University now believe they’ve developed a tool that can potentially save many future victims. The “Chat Analysis Triage Tool (CATT) was developed by professors Kathryn Seigfried-Spellar, Marcus Rogers and Julia Taylor Rayz; essentially, using chatrooms and messages, CATT can filter out and identify predators most likely to pursue face-to-face meetings with children from those more driven by cyber-sex and fantasy. “If we can flag or triage for law enforcement a higher risk of somebody showing up, then in theory, law enforcement might be able to intervene before a sex offense happens,” Seigfried-Spellar said. While the professors won’t reveal every detail behind how CATT works, they are willing to say that the technology uses a combination of natural language processing, psycho-linguistic analysis, content analysis and statistics; which in its simplest form can be describe as breaking down language to analyze intention and producing a sort of “score.” “It’s really doing what a human analyst can do intuitively, and actually doing it with some mathematical formulas, and doing it much faster and in fact more accurate, “Marcus Rogers said. T o calibrate CATT, the professors worked with law enforcement across the country and used around 4,000 real conversations between predators and victims. “It doesn’t care if you spell something wrong, if you spell something with a Harvard education versus a grade school education, that’s all factored in,” Rogers said. Seigfried-Spellar and Rogers say one of the biggest benefits of CATT is the speed and accuracy of which it's able to detect a predator’s intentions. CATT then displays the results and “score” with a simple gas gauge type model. “If we can help create a more efficient process and then potentially stop a sex offense from occurring, I think that’s the ultimate goal here,” Seigfried-Spellar said. The pair say they anticipate testing out CATT with law enforcement agencies within the next few months. It’s possible the tool could be ready by the end of the year. Article The Chat Analysis Triage Tool (CATT) was presented last week by principal investigator Kathryn Seigfried-Spellar, assistant professor of computer and information technology, at the International Association of Law Enforcement Intelligence Analysts Conference in Anaheim, California. Seigfried-Spellar said law enforcement officers are inundated with cases involving the sexual solicitation of minors – some interested in sexual fantasy chats, with others intent on persuading an underage victim into a face-to-face meeting. CATT allows the officers to work through the 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 country. “We went through and tried to identify language-based differences and factors like self-disclosure,” she said. 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. “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,” Seigfried-Spellar said. “That way, officers can begin to prioritize which cases they want to put resources toward to investigate more quickly.” 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. The project started as a result of a partnership with Ventura County Sheriff’s Department in California. 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 computer and information technology department head Marcus Rogers, 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 Link to comment Share on other sites More sharing options...
The Chat Analysis Triage Tool (CATT) was presented last week by principal investigator Kathryn Seigfried-Spellar, assistant professor of computer and information technology, at the International Association of Law Enforcement Intelligence Analysts Conference in Anaheim, California. Seigfried-Spellar said law enforcement officers are inundated with cases involving the sexual solicitation of minors – some interested in sexual fantasy chats, with others intent on persuading an underage victim into a face-to-face meeting. CATT allows the officers to work through the 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 country. “We went through and tried to identify language-based differences and factors like self-disclosure,” she said. 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. “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,” Seigfried-Spellar said. “That way, officers can begin to prioritize which cases they want to put resources toward to investigate more quickly.” 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. The project started as a result of a partnership with Ventura County Sheriff’s Department in California. 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 computer and information technology department head Marcus Rogers, 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
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