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Computational personality assessment

Research output: Contribution to journalJournal articlepeer-review

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  • Clemens Stachl
  • Ryan L Boyd
  • Kai T. Horstmann
  • Poruz Khambatta
  • Sandra C. Matz
  • Gabriella M. Harari
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Article numbere6115
<mark>Journal publication date</mark>15/07/2021
<mark>Journal</mark>Personality Science
Issue number1
Volume2
Number of pages22
Publication StatusPublished
<mark>Original language</mark>English

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.