User Experience: Beyond Cognition and Emotion … Matthias RAUTERBERG

1. User Experience: Beyond Cognition and Emotion … Matthias RAUTERBERG Eindhoven University of Technology – TU/e The Netherlands 2013

2. Interaction Paradigms in Computing Cultural computing Cross cultural-interaction Socialcomputing Community-mediated-interaction Cooperative computing Computer-mediated-interaction Personal computing Man-machine-interaction time 1980 1960 2020 2000 Eindhoven University of Technology

3. What is Culture? Culture is the integration pattern of human behavior that includes - attitudes, - norms, - values, - beliefs, - actions, - communications and language - institutions of a race, ethnic, religious and/or social group. The word culture comes from the Latin root colere (to inhabit, to cultivate, or to honor). In general, it refers to human activity; different definitions of culture reflect different theories for understanding, or criteria for valuing, human activity. Anthropologists use the term to refer to the universal human capacity to classify experiences, and to encode and communicate them symbolically. They regard this capacity as a defining feature of the genus Homo. REF: Rauterberg M. (2006). From personal to cultural computing: how to assess a cultural experience. In: G. Kempter & P. von Hellberg (eds.) uDayIV--Information nutzbar machen (pp. 13-21). Lengerich: Pabst Science Publisher. Eindhoven University of Technology

4. Cultural Computing: Attitudes Norms Values Beliefs Etc. Attitudes Norms Values Beliefs Etc. conscious unconscious Eindhoven University of Technology

5. REF: Salem B., Nakatsu R., Rauterberg M. (2009). Kansei experience: Aesthetic, emotions and inner balance. International Journal on Cognitive Intelligence and Natural Intelligence, vol. 3, no. 2, pp. 18-36. Eindhoven University of Technology

6. Daniel KahnemanMap of Bounded Rationality: A Perspective on Intuitive Judgement and Choice . Nobel Prize Lecture, 8 December 2002 [PDF] Eindhoven University of Technology

7. Sandy PENTLAND Eindhoven University of Technology

8. consciousness* propositional representation* synchronization via global workspace verbal behaviour phenomenal consciousness* internal processing multi modal actuator output nonverbal behaviour unconsciousness* parallel processing in modular subsystems multi modal sensory input REF: Hofmann, W., & Wilson, T. (2010). Consciousness, introspection, and the adaptive unconscious. In B. Gawronski & B. K. Payne (Eds.), Handbook of Implicit Social Cognition: Measurement, Theory, and Applications (pp. 197-215). New York: Guilford Press. Eindhoven University of Technology

9. After 1910 the discoveries of Carl Gustav JUNG about the collective unconscious and the related archetypes were challenging. Jung dreamt a great deal about the dead, the land of the dead, and the rising of the dead. These represented the unconscious itself -- not the "little" personal unconscious that Freud made such a big deal out of, but a new collective unconscious of humanity itself, an unconscious that could contain all the dead, not just our personal ghosts. Jung began to see the mentally ill as people who are haunted by these ghosts, in an age where no-one is supposed to even believe in them. If we could only recapture our mythologies, we would understand these ghosts, become comfortable with the dead, and heal our mental illnesses. (1875-1961) Eindhoven University of Technology

10. Eindhoven University of Technology

11. How to design for the unconscious? A collaborative project between two PhD students Leonid IVONIN Shared activities Huang-Ming CHANG • Processing of physiological signals and application of data mining methods • Development of technical infrastructure for the experiments • Sensing application (ArcheSense) • Generation of ideas • Statistical analysis • Writing of articles • Identification, selection, and preparation of audiovisual stimuli for elicitation of psychological states • Selection of appropriate questionnaires • Presenting application (ArcheBoard) Eindhoven University of Technology

12. The State of the Art Mapping 2.Elicitation 3.Recognition Affective Stimuli Emotional Responses 1.Explicit Emotions (e.g. joy, anger, sadness, etc.) Eindhoven University of Technology

13. The State of the Art Mapping Elicitation Recognition Smile The emotion of Joy Eindhoven University of Technology

14. Problem of Current States What induces emotions? • Perceptual Quality • Black, White • Physical Content • Dove • Symbolic meaning • Peace, Spirit, etc. Appraisal Emotion • Barrett, L. F. (2012). Emotions are real. Emotion, 12(3), 413–29. Eindhoven University of Technology

15. Study 1 - method Hypothesis: Psychological states related to archetypal stimuli would lead to different patterns of physiological activations. • Number of participants: • 34 • Two types of stimuli: • Visual (pictures) • Auditory (sounds) • Five categories of stimuli: • Archetypal • Positive-relaxing • Positive-arousing • Neutral • Negative • Six stimuli per category • Physiological data: • Heart Rate • Galvanic Skin Response • Skin Temperature Examples of visual stimuli The findings indicated a significant relationship between the categories of stimuli (including archetypal) and physiological signals. Eindhoven University of Technology

16. Study 2 - method Hypothesis: Various archetypal experiences lead to recognizable patterns of physiological activations that could be differentiated using computational intelligence algorithms. • Number of participants: • 36 • Two types of stimuli: • Film clips with explicit emotions • Film clips with archetypal experiences • Five categories of explicit stimuli: • Neutral • Amusement • Fear • Joy • Sadness • Physiological data: • ECG (HR + HRV) • Skin conductance (response + level) • Respiration • Skin temperature • Duration of each stimulus: • Approximately 5 minutes • Self-report ratings after every stimulus • Eight categories of archetypal stimuli: • Anima • Animus • Hero departure • Hero initiation • Hero return • Mentor • Mother • Shadow Eindhoven University of Technology

17. Study 2 - results Dynamic patterns of the heart rate responses of the participants to the film clips presentations. The mean values and 95% confidence intervals of the HR are represented with the bold lines and the vertical bars for each of the psychological condition. Eindhoven University of Technology

18. Study 2 - results Classification Performance Achieved with Different Methods Eindhoven University of Technology

19. ArcheSense tool ArcheSense is a tool for evaluation of human experience with products or media based on physiological data of people. A tool for evaluation of unconscious human experience More information about ArcheSense can be found at http://hxresearch.org. Eindhoven University of Technology

20. Study 3 - method Hypothesis: Various archetypal experiences lead to recognizable patterns of physiological activations that could be differentiated using computational intelligence algorithms. • Number of subjects: • 23 • Two types of stimuli: • Film clips with explicit emotions • Film clips with archetypal experiences • Five categories of explicit stimuli: • Neutral • Active-pleasant • Active-unpleasant • Passive-pleasant • Passive-unpleasant • Physiological data: • ECG (HR + HRV) • Skin conductance (response + level) • Duration of each stimulus: • Approximately 1 minute • Number of stimuli per category:3 • Self-report ratings after every stimulus • Seven categories of archetypal stimuli: • Anima • Hero departure • Hero initiation • Hero rebirth • Hero return • Mentor • Mother • Shadow Eindhoven University of Technology

22. Reborn from Fire and Thunder Strom Rain drops down “God is in the rain.” Reborn from Fire Eindhoven University of Technology

23. Study 3 - results Comparison of the classification accuracy achieved using the self-report questionnaires and the physiological data (between-subject classification). Archetypes Explicit emotions Classification methods: k-nearest neighborhood (kNN), support vector machine (SVM), naïve Bayes, linear discriminant analysis (LDA), and Adaptive Boosting with decision trees (AdaBoost). Only the best accuracy is reported. Eindhoven University of Technology

24. Overview Study #1: • ‘Exploratory’ study • Pictures and sounds (presentation for 6 sec) • 1 archetype, 4 explicit emotions • Between-subject design • Statistically significant results • 23.3% classification accuracy (5 classes) Study #2: • Film clips (length 5 min) • 8 archetypes, 5 explicit emotions • 1 stimuli per class • Between-subject design • Statistically significant results • 79.5% classification accuracy (8 classes) Study #3: • Film clips (length 1 min) • 7 archetypes, 5 explicit emotions • 3 stimuli per class • Between-subject and within-subject designs • Statistically significant results • 57.1% classification accuracy (4 classes, between-subject), 70.3% classification accuracy (7 classes, within-subject) Eindhoven University of Technology

25. Performance of Predictive Models Classification Rate in General < = State of the Art Emotion toward Archetypal Symbols Implicit Emotion Eindhoven University of Technology

26. Three main conclusions can be drawn: • Conscious and unconscious reactions are different. • The unconscious is sensitive to archetypes. • The unconsciousness is at least important as the consciousness. Eindhoven University of Technology

27. Thank you for your attention. A door goes open to a new world… Eindhoven University of Technology

28. Publications Downloads at http://www.idemployee.id.tue.nl/g.w.m.rauterberg/references.html#P Journals Ivonin, L., Chang, H.-M., Chen, W., & Rauterberg, M. (2013). Unconscious emotions: Quantifying and logging something we are not aware of. Personal and Ubiquitous Computing, 17(4), 663–673. Conference Chang, H.-M., Ivonin, L., Chen, W., & Rauterberg, M. (2011). Lifelogging for hidden minds: Interacting unconsciously. In J. C. Anacleto, S. Fels, N. Graham, B. Kapralos, M. S. El-Nasr, & K. Stanley (Eds.), Entertainment Computing - ICEC 2011 (LNCS, vol. 6972) (pp. 411–414). Springer Berlin Heidelberg. Chang, H.-M., Ivonin, L., Diaz, M., Catala, A., Chen, W., & Rauterberg, M. (2013). Experience the world with archetypal symbols: A new form of aesthetics. In N. Streitz & C. Stephanidis (Eds.), DAPI/HCII 2013 (LNCS vol. 8028) (pp. 205–214). Springer. Chang, H.-M., Ivonin, L., Chen, W., & Rauterberg, M. (2013). Feeling something without knowing why: Measuring emotions toward archetypal contents. INTETAIN’13 Intelligent Technologies for Interactive Entertainment ( In press). Mons, Belgium. Chang, H.-M., Ivonin, L., Diaz, M., Catala, A., Chen, W., & Rauterberg, M. (2013). What do we feel about archetypes: self-reports and physiological signals. EUSIPCO’13 European Signal Processing Conference ( In press). Marrakech, Morocco. Ivonin, L., Chang, H.-M., Chen, W., & Rauterberg, M. (2012). A new representation of emotion in affective computing. In J. Jia (Ed.), Proceeding of 2012 International Conference on Affective Computing and Intelligent Interaction (Lecture Notes in Information Technology Vol. 10) (pp. 337–343). Taipei, Taiwan: Information Engineering Research Institute. Ivonin, L., Chang, H.-M., Chen, W., & Rauterberg, M. (2013). Automatic recognition of the unconscious reactions from physiological signals. In A. Holzinger (Ed.), SouthCHI 2013 (LNCS Vol. 7946) (pp. 16–35). Springer Berlin Heidelberg.

29. Publications Magazines Ivonin, L.: Measurement and interpretation of consumers’ experiences in neuromarketing. Neuromarketing Theory and Practice. Issue 5 (April), 20-21 (2013) Other Ivonin, L., Chang, H.-M., Chen, W., Rauterberg, M.: Measuring archetypal experiences with physiological sensors. SPIE Newsroom. Online, DOI: 10.1117/2.1201301.004669 (2013) Ivonin, L., Chen, W., Rauterberg, M.: Narratives of Unconscious: Emotion Recognition from Autonomic Reaction Patterns. ICE Summer School Report (2012) Ivonin, L., Chen, W., Rauterberg, M.: Technology for Understanding Human Mind and Behavior. ICE Summer School Report (2011)

30. Submissions under review Journals Chang, H.-M., Ivonin, L., Chen, W., & Rauterberg, M. (2013). From symbolic meanings to emotions: A new strategy for selecting affective stimuli to discover unknown emotions. Psychological Reports, Under review. Chang, H.-M., Ivonin, L., Chen, W., & Rauterberg, M. (2013). From mythology to psychology: Identifying archetypal symbols in movies. Technoetic Arts, (in press). Ivonin, L., Chang, H.-M., Diaz, M., Catala, A., Chen, W., & Rauterberg, M. (2013). Observing archetypal experiences of consumers with physiological measurements. Journal of Consumer Psychology, Under review. Ivonin, L., Chang, H.-M., Diaz, M., Catala, A., Chen, W., & Rauterberg, M. (2013). Beyond cognition and affect: sensing the unconscious. Behaviour and Information Technology, Under review. Conference Chang, H.-M., Ivonin, L., Diaz, M., Catala, A., Chen, W., & Rauterberg, M. (2013). Unspoken emotions in myths: archetypal symbolism as a new resource of emotional design. DPPI‘13 Designing Pleasurable Products and Interfaces. (Under review).