The Murder Accountability
Project (MAP) has developed an algorithm capable of detecting serial killers
who target multiple victims using similar methods of killing within a specific
geographic area. This technique can be useful to police in identifying
difficult-to-see patterns over a period of several years or even decades.
Data visualizations based upon
this algorithm have been added to MAP’s webpage at the “Murder Clusters” tab.
Web users can easily search for possible serial killers without expensive
statistical software or advanced computer knowledge.
The algorithm is based upon a reasonable premise
-- a serial killer can dramatically reduce the normal clearance rate for groups
of similar victims killed through similar methods. The algorithm looks for
clusters with extremely low clearance rates. This algorithm has successfully
detected both well-known serial killers and killers whose homicidal patterns were
not recognized by police.
“We are delighted to provide an online version
of our serial-detection algorithm,” said MAP Chairman Thomas K. Hargrove. “We
hope homicide detectives, police supervisors and the public will use it to
identify threats to community safety.”
MAP believes murder clusters with much-lower-than-expected clearance rates have an elevated probability of containing serial killings. But they are not proof of the presence or absence of multiple-victim offenders.
Rarely are all of the victims within a cluster the handiwork of serial killers. Police investigation – including physical evidence, offender confession, or witness testimony – is the best evidence that a cluster of homicides may be linked.
These visualizations were developed by Haneesh Marella and donated to the Murder Accountability Project. Contact Haneesh through his LinkedIn account here.
