Enhancing Interviewing & Deception Detection Skills In Counter-Terrorism Efforts.

Interactions with the public (eyewitnesses, informants, and those detained both briefly and for longer periods) represent a significant component of law-enforcement and homeland security counter-terrorism efforts. During these interactions, law-enforcement and homeland security personnel will need to make assessments of veracity and deceit, with substantial consequences whether right or wrong. Not only is deception detection and unsolved problem in both counter-terrorism specifically and the social sciences more generally, but only recently has social science research begun testing existing (imperfect) methods of deception detection on individuals from foreign cultures, speaking other languages. This is a critical gap, as this scientific knowledge can be directly applied to the operations of law-enforcement and homeland security personnel in a counter-terrorism context (the interactions mentioned above). The most promising set of techniques for deception detection ? that yield the most impact, for the least cost, in the shortest time-frame ? are narrative analysis techniques (e.g., the Reality Monitoring method).This and other existing narrative analysis techniques used in deception detection (such as criteria-based content analysis, or type-token ratio analysis) show greater potential effectiveness than most other instruments (e.g., the polygraph, facial expression analysis... see DePaulo et al, 2003; NRC Report, 2003); these techniques can be used on a wide range of communications, from first-person interviews to remote communications (such as emails or essays). However, the studies and applications of narrative analysis techniques for deception detection have been almost exclusively amongst English speakers. There are good reasons to believe that significant differences exist between English narratives and those constructed in other languages by non-Western persons (particularly Chinese and Arabic speakers). The author is studying Arabic and Chinese deceptive narratives, to test the effectiveness of narrative analysis techniques in those languages, as well as in English spoken as a second language by native Arabic or Chinese speakers. Further, the author is developing new narrative analysis techniques to suit those tongues where existing methods are inadequate. Finally, the author is adapting existing software for automated natural language processing in order to take advantage of the new cross-cultural/cross-language narrative analysis techniques developed. This will take the form of a prototype to demonstrate the efficacy of the techniques. ..PAT.-Unpublished Manuscript [ABSTRACT FROM AUTHOR]