This research is an in-depth analysis of three multi-channel, multi cue behaviour analysis and or deception detection models.
The importance and uniqueness of this study comes from the evaluation of three distinct approaches – SCAnR (Six Channel Analysis in Real Time), REMAP and BToE (Behavior Table of Elements). The research investigates their characteristic discrepancies, and advocates expanding the scope of behaviour analysis by incorporating new linguistic context.
The main purposes of the research were to compare the three models and elaborate the similarities, distinctions and possible limitations they might have.
The study identified multiple occasions where commonalities and differences have risen such as within their structure system, main concepts and principles or in the more subtle regions, on the behaviour signal level.
A common characteristic led to the identification of possible limitation of the models. This commonality is the language they were created in. This linguistic context can result in limitations when one uses these models’ verbal skillset to identify cues within other languages.
Additionally, the study tested whether SCAnR, BToE, and REMAP can be applied on three distinct linguistic contexts, more precisely a native, a foreign and an adapted language context.
Overall, the analysis confirmed the validity of my hypothesises. These findings also demonstrates that despite the disparities in structure and type of indicators, these models can be a useful and effective tool for deception detection.