Continuous passive sensing of daily behavior from mobile devices has the potential to identify behavioral patterns associated with different aspects of human characteristics. This paper presents novel analytic approaches to extract and understand these behavioral patterns and their impact on predicting adaptive and maladaptive personality traits. Our machine learning analysis extends previous research by showing that both adaptive and maladaptive traits can be predicted from passively sensed behavior providing initial evidence for the utility of this type of data to study personality and its pathology. The analysis also provides insights into the underlying behavior patterns that link adaptive and maladaptive variants consistent with contemporary models of personality pathology. 
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                            Personality Sensing for Theory Development and Assessment in the Digital Age
                        
                    
    
            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 
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                            - Award ID(s):
- 1758835
- PAR ID:
- 10294374
- Date Published:
- Journal Name:
- European Journal of Personality
- Volume:
- 34
- Issue:
- 5
- ISSN:
- 0890-2070
- Page Range / eLocation ID:
- 649 to 669
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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