University of Oulu

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,

When phones get personal : predicting big five personality traits from application usage

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Author: Peltonen, Ella1; Sharmila, Parsa1; Opoku Asare, Kennedy1;
Organizations: 1Center for Ubiquitous Computing, University of Oulu, P.O. Box 4500, FI 90014, Finland
2Department of Computer Science, University of Helsinki, P.O. Box 64, FI 00014, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.4 MB)
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Language: English
Published: Elsevier, 2020
Publish Date: 2020-10-26


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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Series: Pervasive and mobile computing
ISSN: 1574-1192
ISSN-E: 1873-1589
ISSN-L: 1574-1192
Volume: 69
Article number: 101269
DOI: 10.1016/j.pmcj.2020.101269
Type of Publication: A1 Journal article – refereed
Field of Science: 113 Computer and information sciences
Funding: This research is supported by Academy of Finland 6Genesis Flagship (grant 318927), SENSATE (grants 316253, 320089), Infotech Emerging Project, and Nokia Foundation (Jorma Ollila Grant for Dr Ella Peltonen).
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
316253 (Academy of Finland Funding decision)
320089 (Academy of Finland Funding decision)
Copyright information: © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (