Personality Sensing for Theory Development and Assessment in the Digital Age

Abstract

People around the world own digital media devices that mediate and are in close proximity to their daily behaviours and situational contexts. These devices can be harnessed as sensing technologies to collect information from sensor and metadata logs that provide fine‐grained records of everyday personality expression. In this paper, we present a conceptual framework and empirical illustration for personality sensing research, which leverages sensing technologies for personality theory development and assessment. To further empirical knowledge about the degree to which personality‐relevant information is revealed via such data, we outline an agenda for three research domains that focus on the description, explanation, and prediction of personality. To illustrate the value of the personality sensing research agenda, we present findings from a large smartphone‐based sensing study (N = 633) characterizing individual differences in sensed behavioural patterns (physical activity, social behaviour, and smartphone use) and mapping sensed behaviours to the Big Five dimensions. For example, the findings show associations between behavioural tendencies and personality traits and daily behaviours and personality states. We conclude with a discussion of best practices and provide our outlook on how personality sensing will transform our understanding of personality and the way we conduct assessment in the years to come. © 2020 European Association of Personality Psychology

Personality Research and Assessment in the Era of Machine Learning

“…2A detailed description of how ML models work is beyond the scope of this article, so we point readers interested in learning more to the excellent introductory (James et al, 2013; Yarkoni & Westfall, 2017) and advanced resources on the topic (Efron & Hastie, 2016; Hastie et al, 2009). For a detailed treatment of construct validity in the context of ML, we point readers to Bleidorn and Hopwood (2018).…”

Computational Personality Assessment - An Overview and Perspective

“…Furthermore, these internet-connected devices are designed to exchange information for a more convenient user experience (e.g., a smartwatch syncing data to a mobile app). However, the data generated from these technologies can also be harnessed to obtain insights into their owners' behavior (e.g., physical activity, social behavior, digital media use; Harari, Müller, Aung, & Rentfrow, 2017), surrounding environments (e.g., location, ambience; Harari et al, 2018), and personality (Harari et al, 2020;Wiernik et al, 2020). As such, data from sensing technologies present several opportunities for those interested in assessing and understanding the manifestation of personality in daily life.…”

“…To date, personality sensing research has focused on the description, explanation, or prediction of personality-relevant information (Harari et al, 2020). In the domains of description and explanation, studies have focused on individual differences in behavior by providing estimates of the rates of engagement in various behaviors (e.g., calling, texting, using different apps; Budimir et al, 2020;Harari et al, 2019;Schoedel et al, 2018;Stachl et al, 2017), identifying the degree to which such behaviors vary between persons, are stable over time, and map onto self-reported personality traits.…”

“…Research at the intersection of personality psychology and computer science has already begun to harness sources of digital data from online repositories and mobile devices to describe, predict, and better understand individual differences in people's thoughts, feelings, and behavior (e.g., Boyd et al, 2020;Harari et al, 2020). Some of this work has even gone a step further to conceptually explore whether such data can be leveraged for the development of automated computational approaches to personality assessment through predictive modeling (Bleidorn & Hopwood, 2018;Stachl, Pargent, et al, 2020).…”

Investigating the Relationships between Mobility Behaviours and Indicators of Subjective Well–Being Using Smartphone–Based Experience Sampling and GPS Tracking

“…As such, people have been found to visit certain places for the purposes of self and emotion regulation (Silbereisen, Noack, & Eyferth, 1986). For example, places that allow for someone to relax and clear their thoughts have been referred to as restorative places (Korpela, 1991). Restorative places are characterized by their ability to instil a sense of belonging and compatibility void of distractions.…”