@inproceedings{Sarsenbayeva2023MoodAssessment,
	title        = {A Review on Mood Assessment using Smartphones},
	author       = {Sarsenbayeva, Zhanna and Fleming, Charlie and Tag, Benjamin and Withana, Anusha and van Berkel, Niels and McEwan, Alistair},
	year         = 2023,
	booktitle    = {Proceedings of the 19th IFIP TC.13 International Conference on Human-Computer Interaction},
	location     = {INTERACT'23},
	pages        = {to appear},
	abstract     = {Due to their abundance of sensors, today's smartphones can act as a scientific tool to collect contextual information on users' emotional, social, and physical behaviour. With the continuously growing amount of data that can be unobtrusively extracted from smartphones, mood-tracking and inference methods have become more feasible. However, this does raise critical implications for end-users, including accessibility and privacy. Following a structured selection process, we reviewed 32 papers from the ACM Digital Library on mood inference and tracking using smartphones. We conducted an in-depth analysis of used sensors, platform and accessibility, study designs, privacy, self-reporting methods, and accuracy. Based on our analysis, we provide a detailed discussion of the opportunities for research and practice that arise from our findings and outline recommendations for future research within the area of smartphone-based mood tracking and inference.},
	type         = {Conference Paper}
}