Latest revision as of 00:21, 2 February 2021

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.

Original document

The different versions of the original document can be found in:

• http://jultika.oulu.fi/files/nbnfi-fe201702021433.pdf

• http://urn.fi/urn:nbn:fi-fe201702021433

• https://dblp.uni-trier.de/db/conf/huc/ubicomp2016ap.html#VisuriSGKJ16,

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https://findanexpert.unimelb.edu.au/scholarlywork/1201950-impact-of-mood-changes-on-application-selection,

https://doi.acm.org/10.1145/2968219.2968317,

http://jultika.oulu.fi/files/nbnfi-fe201702021433.pdf,

http://jultika.oulu.fi/Record/nbnfi-fe201702021433,

https://dl.acm.org/citation.cfm?id=2968317,

https://dl.acm.org/ft_gateway.cfm?id=2968317&ftid=1787176&dwn=1,

http://opus.bath.ac.uk/51110,

https://academic.microsoft.com/#/detail/2520377849

• https://researchportal.bath.ac.uk/en/publications/impact-of-mood-changes-on-application-selection(21e4dc10-da06-423d-b752-5dfe48806000).html,

https://purehost.bath.ac.uk/ws/files/145770096/frontiersQS2_paper_7.pdf

• http://dl.acm.org/ft_gateway.cfm?id=2968317&ftid=1787176&dwn=1,

http://dx.doi.org/10.1145/2968219.2968317 under the license http://www.acm.org/publications/policies/copyright_policy#Background