Despite the immense capabilities of today’s digital forensic investigation tools, bottlenecks still exist—especially when it comes to abuse, which can be difficult to “prove.” Now, researchers have turned to artificial intelligence (AI) to help.
A team from the University of Huddersfield (UK) has developed a hybrid AI tool to detect patterns of psychological abuse, including coercive control, in a bid to transform digital forensic investigations and mental health research.
This kind of “hidden abuse” is notoriously difficult to capture as evidence because it rarely involves a single violent incident. In addition, evidence of this type of abuse is overwhelmingly digital and standard forensic keyword searches often miss its cumulative nature, such as a pattern of gaslighting, isolation or humiliation.
The Huddersfield team’s solution was to bridge this “data-to-insight gap” by creating a framework they call the Digital Conversation Analysis Pipeline (DCAP), which identifies linguistic indicators of narcissistic abuse cycles, associated psychological manipulation patterns, and related traits in textual data.
DCAP uses a hybrid artificial intelligence approach, combining the precision of rule-based forensic keyword searches with the contextual understanding of a deep learning model to catch things like sarcasm and manipulation, even when it is disguised in modern slang or buzzwords.
In a simulated forensic case of over 8,400 messages, DCAP successfully narrowed this down to 287 key messages containing the most prevalent abusive traits and reduced the investigator's manual review workload by over 92 percent.
DCAP specifically scans for linguistic markers matching the nine diagnostic criteria of Narcissistic Personality Disorder. These are associated with abusive behaviors and include a “lack of empathy” and a “strong sense of entitlement”—vital early-warning signs for investigators tracking patterns of systemic abuse.
The system operates as a “human-in-the-loop,” avoiding black box algorithms and highlighting the exact evidence used to reach its conclusions—a critical part of evidence review once cases get to the courtroom.
“The sheer volume of digital data in modern investigations makes it incredibly difficult for human analysts to spot the subtle, long-term linguistic markers of narcissism and psychological abuse,” said researcher Dhruv Patel, who lead the innovation for his PhD work. “By integrating textual analysis with the evaluation of human emotion via computer vision, we are moving towards a truly multimodal approach. This ensures that no nuance is missed, providing an essential framework for both forensic investigations and complex mental health diagnosis.”
Ultimately, the researchers say the AI tool has the potential to become a powerful asset for police and forensic investigators due to its ability to provide high-fidelity evidence that was previously unreachable, which could be used as expert witness testimony.
The study findings have been published in Forensic Science International: Digital Investigation.