Sophie van der ZeeLecturer
She combines her interest in psychology, law and computer science in her experimental deception and dishonesty research, both in an offline and online context.
Preventing dishonestyPeople like to think of themselves as honest. However, experimental research has demonstrated that most of us lie and cheat on a daily basis. The majority of people lie and cheat a little, just enough to benefit, but not so much that it is no longer possible to justify the dishonest behavior. To which extent people can justify their dishonest behavior and still feel good about themselves differs not only between people, but also between situations. In a recent paper we demonstrated that people are more likely to commit insurance fraud when they feel rejected. Interestingly, they committed fraud even when there were no financial incentives associated with the dishonest act. This finding implies that reducing the chance of rejection, for example by being more transparent about claim acceptance guidelines, can make people more honest and help reduce the cost of fraud. I am currently investigating in what other ways we can nudge people towards honest behavior.
Detecting dishonesty in the real world
The majority of lies are told in a social setting and are not necessarily considered negatively; instead, they may serve as a social glue. Think of what happened to Jim Carrey when he could only speak the truth in Liar Liar. However, in a security setting, it can be critical to correctly assess whether someone is lying. Therefore, researchers have been searching for ways to detect whether a person is lying or being truthful. We developed an automated deception detection method based on body motion. We used full-body motion-capture equipment to objectively determine how much people moved when telling truths and lies. Results revealed that people tend to move more over their entire body when lying. Much research has focused on either determining behavioral differences between truth tellers and liars (i.e., cues to deceit), or magnifying these behavioral differences, for example through inducing cognitive load or interview techniques. Although insights gained from deception research can be useful in security settings, some insights vital to application in the real world are still unknown and need to be addressed.
TeachingSupervising BSc and MSc theses
|M Theeuwes, B van Lier, E Wesselingh, S Van Der Zee, K de Heer & ... (2017) Digitale veiligheid in de regio: Wat zou de rol van veiligheidsregio’s kunnen zijn bij cyberincidenten?. Nationale Veiligheid en Crisisbeheersing 4, 27-29|
|J Jansen, M Junger, J Kort, R Leukfeldt, S Veenstra, J van Wilsem & ... (2017) Victims. Research agenda: The human factor in cybercrime and cybersecurity|
|A Vredeveldt & S Van Der Zee (2017) De betekenis van consistentie in verklaringen. Routes van het recht: Over de rechtspsychologie|
|H Bouma, G Burghouts, R den Hollander, S Van Der Zee, J Baan & ... (2016) Measuring cues for stand-off deception detection based on full-body nonverbal features. SPIE Security+ Defence, 99950M-99950M-20|
|SC van der Zee, R Kleij, JHC van Rest & H Bouma (2016) Actuele ontwikkelingen in leugendetectie. Security Management, Maart, 2|
|S Van Der Zee, R Anderson & R Poppe (2016) When lying feels the right thing to do. Frontiers in psychology 7|
|PJ Taylor, S Tomblin, SM Conchie & S Van Der Zee (2015) Cross-cultural deception detection. Detecting deception: Current challenges and cognitive approaches, 175|
|S Van Der Zee, R Poppe, PJ Taylor & R Anderson (2015) To freeze or not to freeze: A motion-capture approach to detecting deceit. Proceedings of the Hawaii International Conference on System Sciences, Kauai, HI|
|R Poppe, S van der Zee, PJ Taylor, R Anderson & RC Veltkamp (2015) Mining Bodily Cues to Deception. Conference Proceedings of the Rapid Screening Technologies, Deception …|
|R Poppe, S Van Der Zee, DKJ Heylen & PJ Taylor (2014) AMAB: Automated measurement and analysis of body motion. Behavior research methods 46 (3), 625-633|