Computational personality assessment

Stachl, Clemens and Boyd, Ryan L and Horstmann, Kai T. and Khambatta, Poruz and Matz, Sandra C. and Harari, Gabriella M. (2021) Computational personality assessment. Personality Science. ISSN 2700-0710 (In Press)

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Abstract

Innovations in computational methods for the representation and analysis of data have drastically increased the objectivity, reliability, and the practical implications of research conducted throughout most scientific pursuits. Our rapidly-emerging potential to transform digital data into objective measures of human behavior, thoughts, and feelings has perfectly positioned personality science as a critical discipline that will benefit from today’s ongoing digital revolution. Here, we briefly review and discuss some of the most promising sources of data used for computational personality assessment: mobile sensing, online social media, images, language use, and experience sampling. We present a concise overview of key findings, discuss the potential and promise of computational personality assessment, and highlight important remaining questions in their development and application. We conclude with an optimistic outlook on how computational assessment could fuel the transition from personality research to personality science.

Item Type:
Journal Article
Journal or Publication Title:
Personality Science
ID Code:
155892
Deposited By:
Deposited On:
08 Jun 2021 11:04
Refereed?:
Yes
Published?:
In Press
Last Modified:
09 Jun 2021 05:59