An important part of interpreting the PreStudy data is the annotation of the videos taken of the participants. To ease this approach, it is necessary to have a consistent vocabulary and a simplified metric to analyze the emotions.

To generate this metric, the first step was to get information about how other researchers handle emotions. One approach was to view the Games Experience Questionnaire (GEQ) to see which emotions are asked for there. A few examples are happy, annoyed, challenged and content.

Another part is reading literature about this topic and theories about emotions. In the German Wikipedia article about emotion theory it is said that emotion theories are approaches for explaining what emotions are, what cause them and how they influence the behaviour of creatures. Famous researches in emotions are Robert Plutchik, Charles Darwin and Paul Ekman (https://de.wikipedia.org/wiki/Emotionstheorien) .

Paul Ekman classified in his researches following six basic emotions: anger, disgust, fear, happiness, sadness and surprise (https://en.wikipedia.org/wiki/Emotion#Classification).

Robert Plutchik created an emotion wheel, which inspired us for creating our own emotion metric.

(Plutchik's Wheel of Emotions with secondary and tertiary dyads, 2018).

There are several ways of categorizing emotions: classification with the help of the content of the emotions or a classification in a dimensional way: in the psycho physiology they act on the assumption that emotions are compounded of two orthogonal dimensions: arousal and valence. The valence dimension is the one which is important for us: positive / negative (Lang, P., & Bradley, M. (2010), Wilson-Mendenhall, C. D., Barrett, L. F., and Barsalou, L. W. (2013).

We created our own emotion metric for interpreting the emotions of the participants. Therefore we created a list and classified them into negative and positive (-, +). Following, there´s the list of our selected emotions with the classification: Happiness + Sadness - Anger - Frustration - Surprise +/- Resignation - Optimism +

Also, we classified three different intensities of the emotions: low, middle, high (0, 1, 2).

Following, a table which shows an example of a interpreted emotion, is presented:

During this process, a few problems occured: how do we classify surprise, positively or negatively? Solution: it could be both, negative and positive!

Another critical aspect is how to handle laughter? Many times, the participants laugh. On first glance, this makes the interpretation of the emotion easy: laughter is an indicator for fun → ecstasy. But most of the times, the laughter is ironically or a frustrated one, which complicates the annotation. Our solution was to be very careful with the interpretation of the emotions (facial expressions, the situation of laughter) and then decide individually. One example for such an interpretation was:

• https://docs.google.com/forms/d/e/1FAIpQLSfUQFb24nM4kq7lN5ZLM8NX-SkYYRsVUh7U7GmUxTBAoiKNnQ/viewform?fbclid=IwAR3UQGU65AHoxg8hesKbQAfJ2sKBTI4525xKjN9MjtbcYx8_tDnmTDfHaPE
• Stangl, W. (2018). Emotion Psychologische Erklärungsmodelle und Theorien. [werner stangl]s arbeitsblätter. WWW: http://arbeitsblaetter.stangl-taller.at/EMOTION/Emotion.shtml (2018-12-28).)
• Mees, Ulrich (1991). Die Struktur der Emotionen. Göttingen: Hogrefe. Ekman, P. (1973). Darwin and facial expression: A century of research in review. New York: Academic Press. (Stangl, 2018).
• https://de.wikipedia.org/wiki/Emotionstheorien
• https://en.wikipedia.org/wiki/Emotion#Classification
• Lang, P., & Bradley, M. (2010). Emotion and the motivational brain. Biological Psychology, 84(3). doi:10.1016/j.biopsycho.2009.10.007
• Wilson-Mendenhall, C. D., Barrett, L. F., and Barsalou, L. W. (2013). Neural Evidence that human emotions share core affective properties. Psychological Science, 24(6):947–956.
• https://en.wikipedia.org/wiki/Emotion#/media/File:Plutchik_dyads.png