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Reachable but not receptive: enhancing smartphone interruptibility prediction by modelling the extent of user engagement with notifications

Turner, Liam D., Allen, Stuart Michael and Whitaker, Roger Marcus 2017. Reachable but not receptive: enhancing smartphone interruptibility prediction by modelling the extent of user engagement with notifications. Pervasive and Mobile Computing 40 , pp. 480-484. 10.1016/j.pmcj.2017.01.011

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Abstract

Smartphone notifications frequently interrupt our daily lives, often at inopportune moments. We propose the decision-on-information-gain model, which extends the existing data collection convention to capture a range of interruptibility behaviour implicitly. Through a six-month in-the-wild study of 11,346 notifications, we find that this approach captures up to 125% more interruptibility cases. Secondly, we find different correlating contextual features for different behaviour using the approach and find that predictive models can be built with >80% precision for most users. However we note discrepancies in performance across labelling, training, and evaluation methods, creating design considerations for future systems.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
T Technology > T Technology (General)
Uncontrolled Keywords: Interruptibility, notifications, human behaviour, smartphone, mobile
Publisher: Elsevier
ISSN: 1574-1192
Date of First Compliant Deposit: 31 January 2017
Date of Acceptance: 31 January 2017
Last Modified: 29 Jun 2019 16:34
URI: http://orca.cf.ac.uk/id/eprint/97910

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