From marine ecology to crime analysis: improving the detection of serial sexual offences using a taxonomic similarity measure

Jessica Woodhams, Tim D. Grant, Andrew R. G. Price

Research output: Contribution to journalArticlepeer-review

Abstract

Jaccard has been the choice similarity metric in ecology and forensic psychology for comparison of sites or offences, by species or behaviour. This paper applies a more powerful hierarchical measure - taxonomic similarity (s), recently developed in marine ecology - to the task of behaviourally linking serial crime. Forensic case linkage attempts to identify behaviourally similar offences committed by the same unknown perpetrator (called linked offences). s considers progressively higher-level taxa, such that two sites show some similarity even without shared species. We apply this index by analysing 55 specific offence behaviours classified hierarchically. The behaviours are taken from 16 sexual offences by seven juveniles where each offender committed two or more offences. We demonstrate that both Jaccard and s show linked offences to be significantly more similar than unlinked offences. With up to 20% of the specific behaviours removed in simulations, s is equally or more effective at distinguishing linked offences than where Jaccard uses a full data set. Moreover, s retains significant difference between linked and unlinked pairs, with up to 50% of the specific behaviours removed. As police decision-making often depends upon incomplete data, s has clear advantages and its application may extend to other crime types. Copyright © 2007 John Wiley & Sons, Ltd.
Original languageEnglish
Pages (from-to)17-27
Number of pages11
JournalJournal of Investigative Psychology and Offender Profiling
Volume4
Issue number1
DOIs
Publication statusPublished - 1 Jun 2007

Keywords

  • comparative case analysis
  • linkage
  • similarity

Fingerprint

Dive into the research topics of 'From marine ecology to crime analysis: improving the detection of serial sexual offences using a taxonomic similarity measure'. Together they form a unique fingerprint.

Cite this