Studying user behaviour through human-smartphone interactions and experience sampling method data

Noe, Beryl 2020. Studying user behaviour through human-smartphone interactions and experience sampling method data. PhD Thesis, Cardiff University. Item availability restricted.

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Abstract

Nowadays, smartphones are considered ubiquitous with a large share of the global population carrying their phones everywhere and spending significant portions of their day interacting with the device. Due to the high habitual and repetitive usage and the diversity of the activities carried out through the handset, smartphones appear to be a convenient inspective tool to capture and understand human behaviour. In this thesis, we are interested in evaluating an individual’s disposition based on their smartphone usage behaviour. We achieve this through the deployment of the bespoke smartphone app Tymer within a cohort of 64 participants. Following ESM methodology principles, the app was designed to collect various metrics including self-reported mood and unobtrusively recorded low-level UI interaction event data for a period of 8 weeks. In contrast to commonly used alternatives such as inferring the time users spent on their phone or using self-report measures, our novel approach of quantifying smartphone usage based on the number of interaction events provides a more detailed and clearer signal. Using this method, we assess various hypotheses relating to smartphone usage and uncover associations with Smartphone Addiction. Particular significant findings in this domain further motivate the subsequent investigation of the Snapchat app. We also find evidence for the usefulness of smartphone usage behaviours in the prediction of mood states. Our results support the idea that smartphone-human interactions are a valuable proxy for the quantification of smartphone usage behaviours, and that the smartphone is a suitable tool to infer an individual’s disposition, such as their proneness to Smartphone Addiction and their mood.

Item Type:	Thesis (PhD)
Date Type:	Completion
Status:	Unpublished
Schools:	Computer Science & Informatics
Funders:	Cardiff University PSE College
Date of First Compliant Deposit:	25 February 2021
Last Modified:	10 Mar 2021 09:22
URI:	https://orca.cardiff.ac.uk/id/eprint/138925

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