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Behavioral consistency in the digital age

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Behavioral consistency in the digital age. / Shaw, Heather; Taylor, Paul; Ellis, David et al.
In: Psychological Science, Vol. 33, No. 3, 01.03.2022, p. 364-370.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Shaw, H, Taylor, P, Ellis, D & Conchie, S 2022, 'Behavioral consistency in the digital age', Psychological Science, vol. 33, no. 3, pp. 364-370. https://doi.org/10.1177/09567976211040491

APA

Shaw, H., Taylor, P., Ellis, D., & Conchie, S. (2022). Behavioral consistency in the digital age. Psychological Science, 33(3), 364-370. https://doi.org/10.1177/09567976211040491

Vancouver

Shaw H, Taylor P, Ellis D, Conchie S. Behavioral consistency in the digital age. Psychological Science. 2022 Mar 1;33(3):364-370. Epub 2022 Feb 17. doi: 10.1177/09567976211040491

Author

Shaw, Heather ; Taylor, Paul ; Ellis, David et al. / Behavioral consistency in the digital age. In: Psychological Science. 2022 ; Vol. 33, No. 3. pp. 364-370.

Bibtex

@article{cec140e3b77c4ce88528365efc1e71e7,
title = "Behavioral consistency in the digital age",
abstract = "Efforts to infer personality from digital footprints have focused on behavioral stability at the trait level without considering situational dependency. We repeated a classic study of intraindividual consistency with secondary data (five data sets) containing 28,692 days of smartphone usage from 780 people. Using per-app measures of pickup frequency and usage duration, we found that profiles of daily smartphone usage were significantly more consistent when taken from the same user than from different users (d > 1.46). Random-forest models trained on 6 days of behavior identified each of the 780 users in test data with 35.8% accuracy for pickup frequency and 38.5% accuracy for duration frequency. This increased to 73.5% and 75.3%, respectively, when success was taken as the user appearing in the top 10 predictions (i.e., top 1%). Thus, situation-dependent stability in behavior is present in our digital lives, and its uniqueness provides both opportunities and risks to privacy.",
keywords = "Behavioral consistency, Personality, Digital footprint, Intraindividual, Open data, Preregistered",
author = "Heather Shaw and Paul Taylor and David Ellis and Stacey Conchie",
year = "2022",
month = mar,
day = "1",
doi = "10.1177/09567976211040491",
language = "English",
volume = "33",
pages = "364--370",
journal = "Psychological Science",
issn = "0956-7976",
publisher = "SAGE PUBLICATIONS INC",
number = "3",

}

RIS

TY - JOUR

T1 - Behavioral consistency in the digital age

AU - Shaw, Heather

AU - Taylor, Paul

AU - Ellis, David

AU - Conchie, Stacey

PY - 2022/3/1

Y1 - 2022/3/1

N2 - Efforts to infer personality from digital footprints have focused on behavioral stability at the trait level without considering situational dependency. We repeated a classic study of intraindividual consistency with secondary data (five data sets) containing 28,692 days of smartphone usage from 780 people. Using per-app measures of pickup frequency and usage duration, we found that profiles of daily smartphone usage were significantly more consistent when taken from the same user than from different users (d > 1.46). Random-forest models trained on 6 days of behavior identified each of the 780 users in test data with 35.8% accuracy for pickup frequency and 38.5% accuracy for duration frequency. This increased to 73.5% and 75.3%, respectively, when success was taken as the user appearing in the top 10 predictions (i.e., top 1%). Thus, situation-dependent stability in behavior is present in our digital lives, and its uniqueness provides both opportunities and risks to privacy.

AB - Efforts to infer personality from digital footprints have focused on behavioral stability at the trait level without considering situational dependency. We repeated a classic study of intraindividual consistency with secondary data (five data sets) containing 28,692 days of smartphone usage from 780 people. Using per-app measures of pickup frequency and usage duration, we found that profiles of daily smartphone usage were significantly more consistent when taken from the same user than from different users (d > 1.46). Random-forest models trained on 6 days of behavior identified each of the 780 users in test data with 35.8% accuracy for pickup frequency and 38.5% accuracy for duration frequency. This increased to 73.5% and 75.3%, respectively, when success was taken as the user appearing in the top 10 predictions (i.e., top 1%). Thus, situation-dependent stability in behavior is present in our digital lives, and its uniqueness provides both opportunities and risks to privacy.

KW - Behavioral consistency

KW - Personality

KW - Digital footprint

KW - Intraindividual

KW - Open data

KW - Preregistered

U2 - 10.1177/09567976211040491

DO - 10.1177/09567976211040491

M3 - Journal article

VL - 33

SP - 364

EP - 370

JO - Psychological Science

JF - Psychological Science

SN - 0956-7976

IS - 3

ER -