dr. SC (Sophie) van der Zee

Biography

Biography

Dr. Sophie van der Zee has a multi-disciplinary background in psychology, economics, and computer science. She holds a position as assistant professor at the Erasmus School of Economics. She also serves as the academic director of the MSc Behavioural Economics and takes part in Sectorplan SSH-Breed.

Sophie combines this multi-disciplinary background to conduct research on the interplay of human behavior and security. She is specialised in the prevention and detection of deception and dishonest behaviour, both in a face-to-face and online setting. She developed a method for automatically measuring human behavior using motion capture equipment and applied this method to the context of deception detection. She also developed the first personalized deception detection model based on the tweets of former US president Donald Trump. A relevant application area of her research concerns the human factor in cyber, where she investigated how scammers persuade their potential victims, how people put themselves at risk by noncompliance with online banking regulations, and why people do not report cybercrime victimization. In her most recent line of research, she investigates to which extent cyber awareness questionnaires are a useful tool for predicting real world cyber secure behaviour. From a behavioral economics perspective, Sophie also conducts research on promoting sustainable behavior in a hospital context as part of the ESCH-R consortium.

Sophie actively brings deception researchers across the world together. She founded the Deception Research Society. This society organises two types of events. They organise Decepticon, the first interdisciplinary conference on deception. Previous conferences have taken place at the University of Cambridge (UK), Stanford (US), and online. And every first Tuesday of the month, they organise Lies and Allies’ Tuesdays, a free webinar where deception researchers and practitioners from around the world share the latest insights and knowledge.