Impact of mood changes on application selection

Visuri, Aku; Sarsenbayeva, Zhanna; Goncalves, Jorge; Karapanos, Evangelos; Jones, Simon (2016-09-12)
 
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https://doi.org/10.1145/2968219.2968317

Visuri, Aku
Sarsenbayeva, Zhanna
Goncalves, Jorge
Karapanos, Evangelos
Jones, Simon
Association for Computing Machinery
12.09.2016

Aku Visuri, Zhanna Sarsenbayeva, Jorge Goncalves, Evangelos Karapanos, and Simon Jones. 2016. Impact of mood changes on application selection. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct (UbiComp '16). ACM, New York, NY, USA, 535-540. DOI: http://dx.doi.org/10.1145/2968219.2968317

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© Visuri, Sarsenbayeva, Goncalves, Karapanos, Jones | ACM 2016. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct, http://dx.doi.org/10.1145/2968219.2968317
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doi:https://doi.org/10.1145/2968219.2968317
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Abstract

Users of quantified self applications habitually log and track personal information, such as mood. Attempts to automate the procedure of logging mood have been made, but applications themselves rarely provide insights into the user’s mental well-being. In this paper we explore data from two small scale studies related to mobile device usage and mood tracking. We analyse associations between user’s mood throughout the day and the use of smartphone applications from different categories. Our analysis provides insights into the user’s behaviour based on their device usage. These insights mean that QS applications can independently use simple analysis tools to provide similar insights for the user.

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