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Behavioral Consistency in the Digital Age.

Heather ShawPaul J TaylorDavid A EllisStacey M Conchie
Published in: Psychological science (2022)
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.
Keyphrases
  • big data
  • electronic health record
  • climate change
  • physical activity
  • healthcare
  • machine learning
  • dna methylation
  • risk assessment
  • social media
  • high intensity