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Predicting personality from patterns of behavior collected with smartphones

Clemens Stachl, Quay Au, Ramona Schoedel, Samuel D. Gosling, Gabriella M. Harari, Daniel Buschek +6 more
Proceedings of the National Academy of Sci2020CC BY-NC-ND 4.0
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Published articlePublication date: Jul 14, 2020Added to atlas: Oct 15, 2026Source
Citations253Crossref referencesChecked Oct 16, 2026
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Activity counts measure attention, not model quality. Missing counts are unknown. Publication status follows the linked source; a listed venue alone does not confirm peer review.

Stachl and colleagues tested how well Big Five personality dimensions, at both broad domain and narrow facet levels, can be predicted from smartphone-sensed behaviour in a large sample. Six classes of behaviour were used: communication and social behaviour, music consumption, app usage, mobility, overall phone activity, and day- and night-time activity. Communication and social behaviour were the most predictive overall, and the authors highlight both the benefits and the privacy risks of large-scale smartphone data collection.

  • Venue: Proceedings of the National Academy of Sciences
At a glance
Venue
Proceedings of the National Academy of Sciences
Published
2020
DOI
10.1073/pnas.1920484117 (opens in a new tab)
arXiv
Not reported
PMID
Not reported
Licence
CC BY-NC-ND 4.0 (opens in a new tab)
Signals
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Form factor
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Subjects
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Code
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Added
Oct 15, 2026

Abstract

Significance

Smartphones are sensor-rich computers that can easily be used to collect extensive records of behaviors, posing serious threats to individuals’ privacy. This study examines the extent to which individuals’ personality dimensions (assessed at broad domain and narrow facet levels) can be predicted from six classes of behavior: 1) communication and social behavior, 2) music consumption, 3) app usage, 4) mobility, 5) overall phone activity, and 6) day- and night-time activity, in a large sample. The cross-validated results show which Big Five personality dimensions are predictable and which specific patterns of behavior are indicative of which dimensions, revealing communication and social behavior as most predictive overall. Our results highlight the benefits and dangers posed by the widespread collection of smartphone data.

Verbatim fromthe publisher's DOI record· Publisher licence: https://creativecommons.org/licenses/by-nc-nd/4.0/

Predicting personality from patterns of behavior collected with smartphones: ChatPPG research summary card

Cite

@article{stachlpersonalityfromsma2020,
  title = {{Predicting personality from patterns of behavior collected with smartphones}},
  author = {Clemens Stachl and Quay Au and Ramona Schoedel and Samuel D. Gosling and Gabriella M. Harari and Daniel Buschek and Sarah Theres Völkel and Tobias Schuwerk and Michelle Oldemeier and Theresa Ullmann and Heinrich Hussmann and Bernd Bischl et al.},
  year = {2020},
  journal = {Proceedings of the National Academy of Sciences},
  doi = {10.1073/pnas.1920484117}
}

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