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FaceReader Here is a selection of recent publications using FaceReader. If you feel your paper should be on this list, please let us know at [email protected]. Krause, F.; Franke, N. (2023). Understanding Consumer Self-Design Abandonment: A Dynamic Perspective. Journal of Marketing. Märtin, C., Bissinger B.C., & Asta, P. (2021). Optimizing the digital customer journey - Improving user experience by exploiting emotions, personas and situations for individualized user interface adaptations. Journal of Consumer Behavior, 1-12. Bourret, M., Ratelle, C.F., Plamondon, A. & Boisclair Châteauvert, G. (2023). Dynamics of parent-adolescent interactions during a discussion on career choice. Journal of Vocational Behavior, 141. Malfait, A.; Puyvelde, M.; Detaille, F. et al. (2023). Unveiling Readiness of Medical First Responders in Simulation Trainings. AHFE Open Access, vol 116. We compared the results of FaceReader with the intended expressions from the Amsterdam Dynamic Facial Expression Set (ADFES). Our findings? FaceReader has an average accuracy of 99% in measuring the six basic expressions. Read more in our white paper on FaceReader's methodology or check out other validation studies on our resources page. Moreover, FaceReader is by far the most cited facial expression recognition software, with references in over 2,000 peer-reviewed publications.Learn more about FaceReader
Relevant publications
De Wijk, R.; Kaneko, D.; Dijksterhuis, G.; van Bergen, G.; Vingerhoeds, M.; Visalli, M.; Zandstra, E. (2022). A preliminary investigation on the effect of immersive consumption contexts on food-evoked emotions using facial expressions and subjective ratings. Food Quality and Preference.
Talen, L. & den Uyl, T.E. (2021). Complex Website Tasks Increase the Expression Anger Measured with FaceReader Online. International Journal of Human–Computer Interaction.
Hubbard, J.A.; Moore, C.C.; Zajac, L. et al. (2024). The importance of both individual differences and dyadic processes in children's emotion expression. Applied Developmental Science, 28(2): 193–206.
Liu, S.; Wang, Y., Song, Y. (2023). Atypical facial mimicry for basic emotions in children with autism spectrum disorder. Autism Research, 16, 1375-1388.
Zaharieva, M.; Salvadori, E.; Messinger, D.; Visser, I.; Colonnesi, C. (2024). Automated facial expression measurement in a longitudinal sample of 4 and 8 month olds. Behavior Research Methods.
Meng, Q. et al. (2020). On the effectiveness of facial expression recognition for evaluation of urban sound perception. Science of The Total Environment, 710, 135484.
Yang, L.; Chen, X.; Guo, Q. et al. (2022). Changes in facial expressions in patients with Parkinson's disease. Computer Speech & Language, 72(3).Validated in research
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