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Efforts to infer personality from digital footprints have focused on behavioral stability at the trait level without considering situational dependency. We repeat Shoda, Mischel, and Wright’s (1994) classic study of intraindividual consistency with secondary data (5 datasets) 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% / 38.5% (pickup / duration) accuracy. This increased to 73.5% / 75.3% 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.
|Publication status||Acceptance date - 13 Jul 2021|