Dr. Sophie van der Zee is an assistant professor at the Erasmus School of Economics in Rotterdam. She is working with prof. Aurelien Baillon on his ERC starting grant "Bayesian markets for unverifiable truths", investigating how we can elicit more truthful responses from people. She combines her background in psychology and computer science to conduct research within the field of security and human behaviour. Specifically, she has specialised in the prevention and detection of dishonest behaviour, such as lying, cheating, and committing fraud. She developed a method for automatically measuring human behavior using motion capture equipment and applied this method to the context of deception detection. Recently, she conducted a study on the use of the Concealed Information Test for intelligence gathering purposes. In addition to research on deception and dishonesty, Sophie also founded and chairs Decepticon, the first interdisciplinary conference on deceptive behavior. Previous conferences have taken place at the University of Cambridge (UK) and Stanford (US). A relevant application area of her research is concerns the human factor in cyber, where she investigated how scammers persuade their potential victims and how people put themselves at risk by noncompliance with online banking regulations. In her most recent study, she investigates to which extent cyber awareness questionnaires are a useful tool for predicting real world cyber secure behaviour. In addition, Sophie just received a Police & Science grant to start investigating why victims of cybercrime don't tend to report their crimes to the police, and what could help to change that behavior.
M Junger, J Kort, R Leukfeldt, S Veenstra, J van Wilsem & Sophie van der Zee (2017) - Victims - In Research agenda: The human factor in cybercrime and cybersecurity - [link] - Eleven International Publishing
R Poppe, Sophie van der Zee, P J Taylor & R Veltkamp (2015) - Mining bodily cues to deception - In Conference Proceedings of the Rapid Screening Technologies, Deception Detection and Credibility Assessment Symposium