Phone-based metric as a predictor for basic personality traits

TY - JOUR

T1 - Phone-based metric as a predictor for basic personality traits

AU - Mønsted, Bjarke

AU - Mollgaard, Anders

AU - Mathiesen, Joachim

PY - 2018/6/1

Y1 - 2018/6/1

N2 - Basic personality traits are believed to be expressed in, and predictable from, smart phone data. We investigate the extent of this predictability using data (n = 636) from the Copenhagen Network Study, which to our knowledge is the most extensive study concerning smartphone usage and personality traits. Based on phone usage patterns, earlier studies have reported surprisingly high predictability of all Big Five personality traits. We predict personality trait tertiles (low, medum, high) from a set of behavioral variables extracted from the data, and find that only extraversion can be predicted significantly better (35.6%) than by a null model. Finally, we show that the higher predictabilities in the literature are likely due to overfitting on small datasets.

AB - Basic personality traits are believed to be expressed in, and predictable from, smart phone data. We investigate the extent of this predictability using data (n = 636) from the Copenhagen Network Study, which to our knowledge is the most extensive study concerning smartphone usage and personality traits. Based on phone usage patterns, earlier studies have reported surprisingly high predictability of all Big Five personality traits. We predict personality trait tertiles (low, medum, high) from a set of behavioral variables extracted from the data, and find that only extraversion can be predicted significantly better (35.6%) than by a null model. Finally, we show that the higher predictabilities in the literature are likely due to overfitting on small datasets.

U2 - 10.1016/j.jrp.2017.12.004

DO - 10.1016/j.jrp.2017.12.004

M3 - Journal article

SN - 0092-6566

VL - 74

SP - 16

EP - 22

JO - Journal of Research in Personality

JF - Journal of Research in Personality

ER -