When phones get personal : Predicting Big Five personality traits from application usage

As smartphones are increasingly an integral part of daily life, recent literature suggests a deeper relationship between personality traits and smartphone usage. However, this relationship depends on many complex factors such as geographic location, demographics, or cultural influence, just to name a few. These factors provide crucial knowledge for e.g. usage support, recommendations, marketing, general usage improvements. We use six months of application usage data from 739 Android smartphone user together with the IPIP 50-item Big Five personality traits questionnaire. As our main contribution, we show that even category-level aggregated application usage can predict Big Five traits at up to 86%-96% prediction fit in our sample. Our results show the effect of personality traits on application usage (mean error improvement on random guess 17.0%). We also identify which application usage data best describe the Big Five personality traits. Our work enables future personality-driven research, and shows that when studying personality, application categories can provide sufficient predictions in general traits. (C) 2020 The Authors. Published by Elsevier B.V.Peer reviewe

Can personality traits be measured analyzing written language? a meta-analytic study on computational methods

In the last two decades, empirical evidence has shown that personality traits could be related to the characteristics of written language. This study describes a meta-analysis that synthesizes 23 independent estimates of the correlations between the Big Five major personality traits, and some computationally obtained indicators from written language. The results show significant combined estimates of the correlations, albeit small to moderate according to Cohen's conventions to interpret effect sizes, for the five traits (between r = 0.26 for agreeableness and neuroticism, and 0.30 for openness). These estimates are moderated by the type of information in the texts, the use of prediction mechanisms, and the source of publication of the primary studies. Generally, the same effective moderators operate for the five traits. It is concluded that written language analyzed through computational methods could be used to extract relevant information of personality. But further research is still needed to consider it as predictive or explanatory tool for individual difference

Revisión bibliográfica sobre la relación entre la actividad física y la Responsabilidad del Modelo de los Cinco Factores

Este trabajo se propone presentar una revisión bibliográfica que aborda el entrecruzamiento del rasgo Responsabilidad y la práctica de actividad física (AF) y deportiva. Se efectuó una búsqueda en cinco bases de datos y se hallaron 425 artículos publicados entre 1995-2023. Los resultados se sistematizaron en cinco categorías conceptuales que analizan: a) la relación entre Responsabilidad y diferentes formas de AF, b) la combinación de Responsabilidad con otros rasgos para describir la práctica de AF, c) la asociación de las facetas de Responsabilidad con AF, d) la Responsabilidad en el perfil de deportistas y e) las intervenciones que se enfocan en la modificación de los niveles de Responsabilidad o AF basándose en la influencia mutua de ambos constructos. Se espera que este trabajo contribuya en el desarrollo de futuras intervenciones sobre la Responsabilidad para alcanzar niveles de AF con parámetros saludables

Predicting Personality Traits from Physical Activity Intensity

Call and messaging logs from mobile devices have successfully been used to predict personality traits. Yet accelerometer data have not been applied for this purpose. Here we used accelerometer data, along with data from call and messaging logs, to predict five key personality traits