1 School of Psychology, University of Lincoln , Lincoln, United Kingdom .
2 Department of Psychology, Lancaster University , Lancaster, United Kingdom .
Cyberpsychol Behav Soc Netw. 2016 Dec;19(12):727-732. doi: 10.1089/cyber.2016.0324. Epub 2016 Nov 16.
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.
安卓和苹果手机占据了全球所有智能手机销量的 90%以上。尽管在功能上非常相似，但目前的讨论和营销活动表明，这两款设备的用户之间存在关键的个体差异；然而，这从未在经验上得到过验证。这令人惊讶，因为智能手机在各种研究学科中继续获得动力。在本文中，我们考虑这两种不同群体之间是否存在个体差异。与安卓用户相比，我们发现苹果手机用户更有可能是女性、更年轻，并且越来越关注他们的智能手机被视为一种身份象征。个性方面也存在显著差异，苹果手机用户表现出较低的诚实-谦逊和较高的情感性。在进行了这项分析之后，我们还能够构建和测试一个模型，该模型可以基于这些个体差异，以高于随机水平的准确率预测智能手机的拥有情况。与扩展自我理论一致，所拥有的智能手机类型为其拥有者提供了一些有价值的信息。这些发现对智能手机在研究中的日益普及具有重要意义，特别是对于那些在计算社会科学和心理信息学领域工作的人，因为这些领域的数据通常是从运行单一智能手机操作系统的设备和应用程序中收集的。
