Impact of Mood Changes on Application Selection

Aku Visuri; Zhanna Sarsenbayeva; Jorge Goncalves; Evangelos Karapanos; Simon Jones

Impact of Mood Changes on Application Selection

Aku Visuri, Zhanna Sarsenbayeva, Jorge Goncalves, Evangelos Karapanos, Simon Jones

Department of Computer Science

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

11 Citations (SciVal)

174 Downloads (Pure)

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 language	English
Title of host publication	New Frontiers of Quantified Self 2 Workshop @ UbiComp '16
Publisher	Association for Computing Machinery
Publication status	Published - 12 Sept 2016
Event	ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2016) - Heidelberg, Germany Duration: 12 Sept 2016 → 16 Sept 2016

Conference

Conference	ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2016)
Abbreviated title	UbiComp 2016
Country/Territory	Germany
Period	12/09/16 → 16/09/16

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frontiersQS2_paper_7Accepted author manuscript, 441 KBLicence: Unspecified

Cite this

@inproceedings{21e4dc10da06423db7525dfe48806000,

title = "Impact of Mood Changes on Application Selection",

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{\textquoteright}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{\textquoteright}s mood throughout the day and the use of smartphone applications from different categories. Our analysis provides insights into the user{\textquoteright}s behaviour based on their device usage. Theseinsights mean that QS applications can independently use simple analysis tools to provide similar insights for the user.",

author = "Aku Visuri and Zhanna Sarsenbayeva and Jorge Goncalves and Evangelos Karapanos and Simon Jones",

year = "2016",

month = sep,

day = "12",

language = "English",

booktitle = "New Frontiers of Quantified Self 2 Workshop @ UbiComp '16",

publisher = "Association for Computing Machinery",

address = "USA United States",

note = "ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2016), UbiComp 2016 ; Conference date: 12-09-2016 Through 16-09-2016",

}

TY - GEN

T1 - Impact of Mood Changes on Application Selection

AU - Visuri, Aku

AU - Sarsenbayeva, Zhanna

AU - Goncalves, Jorge

AU - Karapanos, Evangelos

AU - Jones, Simon

PY - 2016/9/12

Y1 - 2016/9/12

N2 - 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. Theseinsights mean that QS applications can independently use simple analysis tools to provide similar insights for the user.

AB - 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. Theseinsights mean that QS applications can independently use simple analysis tools to provide similar insights for the user.

M3 - Chapter in a published conference proceeding

BT - New Frontiers of Quantified Self 2 Workshop @ UbiComp '16

PB - Association for Computing Machinery

T2 - ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2016)

Y2 - 12 September 2016 through 16 September 2016

ER -

Impact of Mood Changes on Application Selection

Abstract

Conference

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