When phones get personal : predicting big five personality traits from application usage
Peltonen, Ella; Sharmila, Parsa; Opoku Asare, Kennedy; Visuri, Aku; Lagerspetz, Eemil; Ferreira, Denzil (2020-10-10)
Ella Peltonen, Parsa Sharmila, Kennedy Opoku Asare, Aku Visuri, Eemil Lagerspetz, Denzil Ferreira, When phones get personal: Predicting Big Five personality traits from application usage, Pervasive and Mobile Computing, Volume 69, 2020, 101269, ISSN 1574-1192, https://doi.org/10.1016/j.pmcj.2020.101269
© 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
https://creativecommons.org/licenses/by-nc-nd/4.0/
https://urn.fi/URN:NBN:fi-fe2020102687660
Tiivistelmä
Abstract
As smartphones are increasingly an integral part of daily life, recent literature suggests a deeper relationship between personality traits and smartphone usage. However, this relationship depends on many complex factors such as geographic location, demographics, or cultural influence, just to name a few. These factors provide crucial knowledge for e.g. usage support, recommendations, marketing, general usage improvements. We use six months of application usage data from 739 Android smartphone user together with the IPIP 50-item Big Five personality traits questionnaire. As our main contribution, we show that even category-level aggregated application usage can predict Big Five traits at up to 86%–96% prediction fit in our sample. Our results show the effect of personality traits on application usage (mean error improvement on random guess 17.0%). We also identify which application usage data best describe the Big Five personality traits. Our work enables future personality-driven research, and shows that when studying personality, application categories can provide sufficient predictions in general traits.
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