Helma Torkamaan, Jürgen Ziegler
A growing number of studies in the computer science and engineering communities are addressing mood, an affective phenomenon related but not equivalent to emotion. While emotion has been investigated intensely in the affective computing domain, the characteristics and applications of mood are relatively unexplored. Through a bottom-up approach, this paper aims to identify in which areas and for what purposes computer scientists and other researchers in the ACM and IEEE communities are studying mood. Based on a literature review of 1,264 peer-reviewed publications, this paper proposes a taxonomy of mood research in affective computing. Despite a wide range of applications and domains, core themes of mood research relate to identifying users’ mood, influencing it, or helping users to communicate their mood to others. The conceptualization and definition of mood, however, vary between the studies surveyed and sometimes can fall considerably far from the psychological concept of mood in affect research. In several instances, researchers use the terms mood and emotion interchangeably and do not sufficiently discuss the implications both for their measurements and for the design of affective-computing systems as well. With our study, we aim to contribute a clearer conceptualization of mood research and to provide researchers with a broad overview of the research as well as areas of applications in which mood is addressed.
Helma Torkamaan and and Jürgen Ziegler. 2017. A taxonomy of mood research and its applications in computer science, in 2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII), pp. 421-426, doi: 10.1109/ACII.2017.8273634.