Abstract
Affective Computing has always aimed to answer the question: which measurement is most suitable to predict the subject’s affective state? Many experiments have been devised to evaluate the relationships among three types of variables (the affective triad): stimuli, self-reports, and measurements. Being the real affective state hidden, researchers have faced this question by looking for the measure most related either to the stimulus, or to self-reports. The first approach assumes that people receiving the same stimulus are feeling the same emotion; a condition difficult to match in practice. The second approach assumes that emotion is what people are saying to feel, and seems more likely.
We propose a novel method, which extends the mentioned ones by looking for the physiological measurement mostly correlated to the self-report due to emotion, not the stimulus. This guarantees to find a measure best related to subject’s affective state.
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Tognetti, S., Garbarino, M., Matteucci, M., Bonarini, A. (2011). The Affective Triad: Stimuli, Questionnaires, and Measurements. In: D’Mello, S., Graesser, A., Schuller, B., Martin, JC. (eds) Affective Computing and Intelligent Interaction. ACII 2011. Lecture Notes in Computer Science, vol 6975. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24571-8_11
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DOI: https://doi.org/10.1007/978-3-642-24571-8_11
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