Computational Assessment of Psychological Characteristics: Future Perspectives
Year: 2025
Type: preprint
Abstract: Digital traces and machine learning methods are transforming psychometric assessment by enabling the ecological study of psychological characteristics in everyday life. However, past research has predominantly focused on predicting the Big Five personality traits, leaving vast areas of human psychology unexplored. Emerging findings from computer science suggest the feasibility of computational assessments beyond the Big Five, but are often limited by their reliance on public digital traces from social media. This article outlines future directions for developing more interpretable, robust, and valid computational assessments that integrate psychological theory with the versatility of digital trace data. Applying this theoretical lens, promising avenues beyond Big Five traits are identified across a wide range of constructs conceptualizing differences in personality, ability, motivation, and evaluation. As computational psychological assessment continues to evolve, psychologists will be essential in realizing its potential while identifying its conceptual and methodological boundaries.
Author: Maximilian Bergmann
Language: English
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: gold
OpenAlex ID: W4413233191