Personality Trait Recognition Based on Smartphone Typing Characteristics in the Wild

Kovacevic N, Holz C, Günther T, Gross M, Wampfler R (2023)

Publication Type: Journal article

Publication year: 2023

Journal

IEEE Transactions on Affective Computing Institute of Electrical and Electronics Engineers

Pages Range: 1-11

DOI: 10.1109/TAFFC.2023.3253202

Abstract

As governed by personality trait theory, humans tackle problems differently depending on their long-term behavioral characteristics. Computational awareness of personality traits fuels affective computing research, which investigates how to reliably recognize and utilize personality traits. Applications are diverse, including therapy monitoring, learning assistance, and recommender systems. Data-driven approaches are a promising path forward towards personality-aware human-computer interactions. Thereby, central challenges are the non-disruptive data acquisition, the time frame over which data must be collected before predictions become accurate, and the feature-centered data reduction to train reliable and lightweight machine learning models. In this work, we address these challenges by presenting a fully-automatic feature extraction and machine learning pipeline that makes accurate personality trait predictions for the widely-used Five Factor Model from passively-collected, short-term smartphone typing data collected from 76 participants (68 university students) in the wild. Our model allows for personality trait assessments after one day of data collection, demonstrating that, despite being a long-term behavioral trend, personality traits can be inferred accurately from shorter time periods. We demonstrate that our system can accurately predict personality traits on two levels (low and high) with up to 74.5% accuracy and 0.72 AUC for a single day, and up to 84.5% accuracy and 0.79 AUC after subsequent refinement over 10 weeks.

Authors with CRIS profile

Tobias Günther Professur für Visual Computing

Involved external institutions

Eidgenössische Technische Hochschule Zürich (ETHZ) / Swiss Federal Institute of Technology in Zurich

Switzerland (CH)

How to cite

APA:

Kovacevic, N., Holz, C., Günther, T., Gross, M., & Wampfler, R. (2023). Personality Trait Recognition Based on Smartphone Typing Characteristics in the Wild. IEEE Transactions on Affective Computing, 1-11. https://dx.doi.org/10.1109/TAFFC.2023.3253202

MLA:

Kovacevic, Nikola, et al. "Personality Trait Recognition Based on Smartphone Typing Characteristics in the Wild." IEEE Transactions on Affective Computing (2023): 1-11.

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