Dr. Matthias Unfried
Senior Researcher // Research Program Manager Decision Labs
Matthias is an economist by training with a strong focus on microeconomics. Hence, his main field of interest are economic decisions and the related behavior of market actors. Especially the question what drives – and probably biases – individual decisions is in the focus of his research.
In the past years, he mainly explored and developed methods for the automatic detection of emotions, especially the inference of emotions from a person’s voice. Furthermore, he worked on implicit methods of data collection and the methods of behavioral economics in market research contexts.
His current focus is behavioral and experimental economics. In particular, he is interested in decision making processes in environments with automatic, algorithm-based decision systems and the role of social norms in such environments. Moreover, he is the contact for the mobile decision lab in Nuremberg as well as the „Prosumer Decision Labs“, which are part of a network including labs jointly established with the University of Pretoria, and the Business Shool of the Central University of Finance and Economics (CUFE) in Beijing.
- Contact for the Decision Labs
- Affect and Decision Making
- Decisin Support Systems
- Nuremberg Institute for Market Decisions, Program Manager Market Decision Labs /// Senior Researcher
- GfK Verein, Research
- PhD (Dr. rer. pol.) in Economics with focus on Microeconomics, applied Game Theory and market modelling
- Research Assistant at the Chair of Economic Theory (Prof. Veronika Grimm), University of Erlangen-Nuremberg
- Diploma in Economics, Universität Erlangen-Nürnberg
Publications in Journals and Conference Proceedings:
- Scherer, K. R., Mortillaro, M., Dieckmann, A., Unfried M. & Ellgring, H., (2019), Investigating appraisal-driven facial expression and inference in emotion communication, Emotion, Advance online publication. https://doi.org/10.1037/emo0000693.
- Scherer, K. R., Ellgring, H., Dieckmann, A., Unfried M. & Mortillaro M. (2019), Dynamic facial expression of emotion and observer inference, Frontiers in Psychology 10:508.
- Eyben, F., Unfried, M., Hagerer, G. & Schuller, B. (2017), Automatic Multi-lingual Arousal Detection from Voice Applied to Real Product Testing Applications. Proceedings 42nd IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 5155-5159.
- Dieckmann, A., Grimm, V., Unfried, M., Utikal, V., & Valmasoni, L. (2016). On Trust in Honesty and Volunteering among Europeans: Cross-Country Evidence on Perceptions and Behavior. European Economic Review 90, 225-253.
- Garbas, J. U., Ruf, T., Unfried, M., & Dieckmann, A. (2013). Towards Robust Real-time Valence Recognition from Facial Expressions for Market Research Applications. Affective Computing and Intelligent Interaction (ACII), 2013 Humaine Association Conference on, 570-575.
- Leepa, C., & Unfried, M. (2013). Effects of a cut-off in feed-in tariffs on photovoltaic capacity: Evidence from Germany. Energy Policy, 56, 536-542.
Publications in GfK Verein Publication Series:
- Lotta Blum, Anja Dieckmann & Matthias Unfried (2020). Confusion can improve cognitive performance: An ex-perimental study using automatic facial expression analysis. NIM Working Paper Series, No. 8 / 2020.
- Dieckmann, A., Unfried, M., Schreder, R., Kissel, K. (2018), How valid are response-time measures for capturing implicit brand attitudes?, GfK Verein Working Paper Series, No. 7 / 2018.
- Dieckmann, A., Unfried, M., Garbas J., Mortillaro, M. (2017), Automatic analysis of facial expressions in an advertising test with Chinese respondents, GfK Verein Working Paper Series, No. 5 / 2017.
- Frank, R., Unfried, M., Schreder, R. & Dieckmann, A. (2016). Ethical textile consumption: Only a question of selflessness? Marketing Intelligence Review, 8(1), 52-58.
- Unfried, M. & Iwanczok, M. (2016). Improving signal detection in software-based facial expression analysis. GfK Verein Working Paper Series, No. 1 / 2016.
- Dieckmann, A. & Unfried, M. (2014). Writ Large on Your Face: Observing Emotions Using Automatic Facial Analysis. Marketing Intelligence Review, 6(1), 52-58.