Abstract
Effective and frequent sampling of mood through self-reports could enable a better understanding of the interplay between mood and events influencing it. To accomplish this, we built a mobile application featuring a sadness-happiness visual analogue scale and a facial expression-based scale. The goal is to evaluate, whether a facial expression based scale could adequately capture mood. The method and mobile application were evaluated with 11 participants. They rated the mood of characters presented in a series of vignettes, using both scales. Participants also completed a user experience survey rating the two assessment methods and the mobile interface. Findings reveal a Pearson’s correlation coefficient of 0.97 between the two assessment scales and a stronger preference for the face scale. We conclude with a discussion of the implications of our findings for mood self-assessment and an outline future research.
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Acknowledgment
This work has been supported by AffecTech: Personal Technologies for Affective Health, Innovative Training Network funded by the H2020 People Programme under Marie Skłodowska-Curie grant agreement No. 722022.
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Valev, H., Leufkens, T., Sas, C., Westerink, J., Dotsch, R. (2019). Evaluation of a Self-report System for Assessing Mood Using Facial Expressions. In: Cipresso, P., Serino, S., Villani, D. (eds) Pervasive Computing Paradigms for Mental Health. MindCare 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 288. Springer, Cham. https://doi.org/10.1007/978-3-030-25872-6_19
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