Utilising the co-occurrence of user interface interactions as a risk indicator for smartphone addiction

The push to a connected world where people carry an always-online device which has been designed to maximise instant gratification and prompts users via notifications has lead to a surge of potentially problematic behaviour as a result. This has lead to a rising interest in addressing and understanding the addictiveness of smartphone usage, as well as for particular applications (apps). However, capturing addiction from usage involves not only assessment of potential addiction risk but also requires understanding of the complex interactions that define user behaviour and how these can be effectively isolated and summarised. In this paper, we examine the correlation of physical user interface (UI) interactions (e.g. taps and scrolls) and smartphone addiction risk using a large dataset of those smartphone events (65,093,343, N=301,024 sessions) collected from 64 users over an 8-week period with an accompanying smartphone addiction survey. Our novel method which reports on the probability of a users addiction risk and in a model case we show how it was be used to identify 57 of 64 users correctly. This supports our observations of UI events during sessions of usage being indicative of addiction risk while improving previous approaches which rely on summative data such as screen on time. Within this we also find that users only exhibit addictive behaviour in a subset of all sessions while using their smartphone. •Smartphone addiction risk can be assessed via analysis of UI events within sessions.•Term weighted co-occurrence of events outperforms existing measures as an indicator.•Evaluating 65 million UI events within 141,588 sessions over 8 weeks from 64 users.•Users with a high addiction risk only exhibit behaviour in a subset of sessions.