Stachl, Clemens and Pargent, Florian and Hilbert, Sven and Harari, Gabriella M. and Schoedel, Ramona and Vaid, Sumer and Gosling, Samuel D. and Buehner, Markus (2020) Personality Research and Assessment in the Era of Machine Learning. EUROPEAN JOURNAL OF PERSONALITY, 34 (5). pp. 613-631. ISSN 0890-2070, 1099-0984
Full text not available from this repository. (Request a copy)Abstract
The increasing availability of high-dimensional, fine-grained data about human behaviour, gathered from mobile sensing studies and in the form of digital footprints, is poised to drastically alter the way personality psychologists perform research and undertake personality assessment. These new kinds and quantities of data raise important questions about how to analyse the data and interpret the results appropriately. Machine learning models are well suited to these kinds of data, allowing researchers to model highly complex relationships and to evaluate the generalizability and robustness of their results using resampling methods. The correct usage of machine learning models requires specialized methodological training that considers issues specific to this type of modelling. Here, we first provide a brief overview of past studies using machine learning in personality psychology. Second, we illustrate the main challenges that researchers face when building, interpreting, and validating machine learning models. Third, we discuss the evaluation of personality scales, derived using machine learning methods. Fourth, we highlight some key issues that arise from the use of latent variables in the modelling process. We conclude with an outlook on the future role of machine learning models in personality research and assessment.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | DIGITAL FOOTPRINTS; SOCIAL MEDIA; IRT MODELS; TRAITS; ACCURATE; STYLE; assessment; interpretability; machine learning; overfitting; personality |
| Subjects: | 300 Social sciences > 370 Education |
| Divisions: | Human Sciences > Institut für Bildungswissenschaft Human Sciences > Institut für Bildungswissenschaft > Professur für Methoden der empirischen Bildungsforschung - Prof. Dr. Sven Hilbert |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 23 Mar 2021 09:29 |
| Last Modified: | 23 Mar 2021 09:29 |
| URI: | https://pred.uni-regensburg.de/id/eprint/44516 |
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