LOS ANGELES, April 21 (Xinhua) -- Researchers at Purdue Polytechnic Institute have developed an algorithm tool that may help law enforcement 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 presented recently 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.
The tool allows law enforcement officers to work through a volume of sexual solicitations and use algorithms to examine the word usage and conversation patterns of a suspect. The data was taken from online conversations provided voluntarily by law enforcement around the United States, according to researchers.
"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, as quoted by the university's press release.
"That way, officers can begin to prioritize which cases they want to put resources toward to investigate more quickly," she said.
The project started as the result of a partnership with the Ventura County Sheriff's Department in California and began with initial research done by Seigfried-Spellar and a former professor. The findings of the research will be published in the journal "Child Abuse and Neglect."
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 then determined through this research formed the basis for CATT. Seigfried-Spellar said CATT could be handling data from active cases as early as the end of the year.
According to researchers, CATT algorithms examine only the conversation factors and do not take the sex of either suspect or victim into consideration, at this time.
The conversation analysis provides the basis for future law enforcement tools as well, Seigfried-Spellar said.
