Affiliation:
1. Tel Aviv University, Department of Industrial Engineering
2. The Max Stern Yezreel Valley Academic College / Tel Aviv University Lambda Lab
3. Afeka Tel-Aviv Academic College of Engineering Industrial Engineering and Management Department / Tel Aviv University Lambda Lab
Abstract
Abstract
Digital Phenotyping (DP) entails exploring digital expressions of human personality using behavioral cues drawn from smartphones’ digital footprints. Most personality-oriented DP studies focus narrowly on the Big5 model. This research aims to broaden this approach, using fifty-four personality constructs rooted in fifteen leading personality theories beyond the Big5. Our sample consisted of 104 respondents from whom smartphone data was collected over 7–10 days. We implemented both deductive (hypothesis-testing) and inductive (machine learning) modelling methods. Results show that fifteen of the sixteen broad personality constructs were successfully predicted from smartphone data (forty-eight sub-personality items of the fifty-nine types and personality traits). The best overall predictive model was Gradient Boosted Trees with communication-related features having the highest predictive weight. DP has the potential to transform the field of personality research and may be applied in areas such as HR analytics, personality-based targeted marketing, individualized homeland security, financial risk assessments, personalized medicine, and more.
Publisher
Research Square Platform LLC
Reference99 articles.
1. Toward a biological basis of the FFM Meta-traits: Associations between the Fisher Type Indicator (FTI) temperament construct and the hierarchical Five Factor Model (FFM) of personality;Alkalay S;Personality and Individual Differences,2022
2. Predicting depression from smartphone behavioural markers using machine learning methods, hyperparameter optimization, and feature importance analysis: exploratory study;Asare KO;JMIR mHealth and uHealth,2021
3. A human resources analytics and machine-learning examination of turnover: implications for theory and practice;Avrahami D;International Journal of Manpower,2022
4. AWARE – Open-source Context Instrumentation Framework for Everyone. (2022). Retrieved 27 August 2022, from https://awareframework.com/
5. Bandura, A., Freeman, W. H., & Lightsey, R. (1999). Self-efficacy: The exercise of control.