New Dutch emotion research

mona lisa analyzedPeter Lewinski, Marieke Fransen and Ed Tan recently made the headlines with the results of their research into automated facial coding of emotions. ACCESS asked Peter Lewinski to tell us more about his project and he kindly sent us this description of the research.

We welcome news about Dutch emotion research on our website – please contact k[dot]steenbergh[at]vu[dot]nl if you would like to share your project with our community.

MEASURING EMOTIONAL ATTITUDES WITH AUTOMATED FACIAL CODING

Nonverbal communication of emotions

Suppose you want to sell your home-made jewelry at the King’s day in Amsterdam. How can you tell in advance whether people like your necklaces and ear rings? Since the earliest scientific inquiries into preferences the only available method has been to ask people how they feel about them. However psychologists found out that when you are asked about your opinion you tend to become self-aware and start to provide socially desirable answers. In other words self-reports emanate from Daniel Kahneman’s –System 2 and this is as slow and logical as it is conscious System. Questionnaires and interviews capture creations and interpretations led by self and social reflective human judgment. The contents of the fast, emotional and subconscious System 1 have long remained elusive. Even if messages delivered by System 1 are ubiquitous in people’s everyday non-verbal behavior, such as gestures, postures, facial expressions and tone of voice. Decoding the messages has been hampered or even forbidden by the subjective and laborious nature of analyses. In the past decade information technology and artificial intelligence have come to the rescue of the direct measurement of emotions. Hopes are high that we can leave considerable work load required for codification of nonverbal behavior to the computer and so steer away from our own interpretation biases. The research community working on the deciphering of facial movements believes that facial expressions convey interculturally shared core affect signatures. They do not need cross-cultural translation as System 2 responses – notably verbal ones – do. Therefore, in our study, recently published in Journal of Neuroscience, Psychology, and Economics, we investigated the predictive value of facial expressions of emotions in response to amusing – i.e. simply funny – video stimuli. Continue reading →