Abstract
Computational methods have increased the objectivity of measures of human behavior and positioned personality science to benefit from the ongoing digital revolution. In this review, we define and discuss computational personality assessment (CPA), a measurement process that uses computational technologies to obtain estimates of personality. We briefly review some of the most promising sources of data currently used for CPA: mobile sensing, digital footprints from social media, images, language, and experience sampling. We present a concise overview of key findings, discuss the promise and opportunities of CPA (e.g., moving towards objective measures of personality, obtaining new insights from big data), and highlight important limitations and challenges in the development and application of CPA (e.g., establishing reliability and validity, selecting appropriate ground truth criterion, assessing affect and cognition, implications for ethics and privacy). We conclude with our perspective on how CPA could change our understanding of individual differences.
Highlights
Computational methods have increased the objectivity of measures of human behavior and positioned personality science to benefit from the ongoing digital revolution
We briefly review some of the most promising sources of data currently used for computational personality assessment (CPA): mobile sensing, digital footprints from social media, images, language, and experience sampling
Computational personality assessment based on digital footprints and high frequent behavioral data from in-vivo sensing studies could drastically change the concept of personality and its assessment
Summary
Computational methods have increased the objectivity of measures of human behavior and positioned personality science to benefit from the ongoing digital revolution. We present a concise overview of key findings, discuss the promise and opportunities of CPA (e.g., moving towards objective measures of personality, obtaining new insights from big data), and highlight important limitations and challenges in the development and application of CPA (e.g., establishing reliability and validity, selecting appropriate ground truth criterion, assessing affect and cognition, implications for ethics and privacy). Computational personality assessment based on digital footprints and high frequent behavioral data from in-vivo sensing studies could drastically change the concept of personality and its assessment. One of the most profound changes that has broadly affected psychological science is the ongoing shift towards computational measurement and assessment
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