MoodScope: building a mood sensor from smartphone usage patterns

By Robert LiKamWa, Yunxin Liu, Nicholas Donald Lane, Lin Zhong. ACM SIGMOBILE International Conference on Mobile Systems, Applications, and Services, 2013

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Psychological targeting as an effective approach to digital mass persuasion (2017, background): “For example, people’s mood and emotions have been successfully assessed from spoken and written language (30), video (31), or wearable devices and smartphone sensor data (32).”
Emotion recognition using wireless signals (2016, background): “) to infer user daily mood or personality [39, 15]; however, these techniques operate at much large time scales (days or months) than EQ-Radio, which recognizes emotions at minute-scale intervals.”
Trajectories of depression: unobtrusive monitoring of depressive states by means of smartphone mobility traces analysis (2015, background): “In particular, in the pervasive and ubiquitous computing community, several projects have investigated the use of smartphone data for the automatic detection and prediction of psychological states and mental health conditions [22, 32, 23, 6].”
Mood measurement with Pick-A-Mood: review of current methods and design of a pictorial self-report scale (2016, unknown): “Affect (stress and relaxation) can be detected from keyboard (Hernandez et al., 2014), pen (Alonso et al., 2008), mouse (Sun et al., 2014), or smartphone usage behaviours (LiKamWa et al., 2013).”