University of Hertfordshire

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Original languageEnglish
Number of pages6
Pages (from-to)727-732
JournalCyberpsychology, Behavior, and Social Networking
Journal publication date1 Dec 2016
Volume19
Issue12
Early online date16 Nov 2016
DOIs
StatePublished - 1 Dec 2016

Abstract

Android and iPhone devices account for over 90 percent of all smartphones sold worldwide. Despite being very similar in functionality, current discourse and marketing campaigns suggest that key individual differences exist between users of these two devices; however, this has never been investigated empirically. This is surprising, as smartphones continue to gain momentum across a variety of research disciplines. In this article, we consider if individual differences exist between these two distinct groups. In comparison to Android users, we found that iPhone owners are more likely to be female, younger, and increasingly concerned about their smartphone being viewed as a status object. Key differences in personality were also observed with iPhone users displaying lower levels of Honesty-Humility and higher levels of emotionality. Following this analysis, we were also able to build and test a model that predicted smartphone ownership at above chance level based on these individual differences. In line with extended self-theory, the type of smartphone owned provides some valuable information about its owner. These findings have implications for the increasing use of smartphones within research particularly for those working within Computational Social Science and PsychoInformatics, where data are typically collected from devices and applications running a single smartphone operating system.

Notes

This document is the Accepted Manuscript of the following article: Shaw Heather, Ellis David A., Kendrick Libby-Rae, Ziegler Fenja, and Wiseman Richard. Cyberpsychology, Behavior, and Social Networking. December 2016, 19(12): 727-732. Under embargo. Embargo end date: 16 November 2017. The final publication is available from Mary Ann Liebert, Inc., publishers, at: https://doi.org/10.1089/cyber.2016.0324

ID: 11089972