Personality Trait Recognition Based on Smartphone Typing Characteristics in the Wild

Jan 1, 2023·
N. Kovačević
,
C. Holz
,
T. Günther
,
M. Gross
Dr. Rafael Wampfler
Dr. Rafael Wampfler
Abstract
We demonstrate that personality traits — specifically the Big Five dimensions of openness, conscientiousness, extraversion, agreeableness, and neuroticism — can be reliably inferred from passive observation of smartphone typing behavior in naturalistic conditions. Using a longitudinal dataset of keyboard dynamics collected during everyday device use, we develop deep learning models that extract typing features including keystroke timing, pressure, finger size, and rhythm patterns, and map them to personality scores validated against established psychometric measures. Our in-the-wild evaluation shows that typing-based personality recognition achieves meaningful predictive accuracy without requiring explicit user input, with implications for passive human-computer interaction modeling and personalized computing.
Type
Publication
IEEE Transactions on Affective Computing
publications
Personality Recognition Mobile Sensing Typing Dynamics Affective Computing In-the-Wild
Dr. Rafael Wampfler
Authors
Dr. Rafael Wampfler
Senior Researcher & Lecturer

I am a Senior Researcher & Lecturer at the Computer Graphics Laboratory of ETH Zurich, and a Research Consultant at Disney Research. I am leading the Digital Character AI projects at CGL. My research interests include conversational digital characters, affective computing, human-computer interaction, and applied machine learning.

My vision is to create intelligent digital humans that can naturally communicate, understand, and support people across domains such as education and mental health. My research focuses on multimodal artificial intelligence for interactive digital humans, developing models that combine large language models, affective computing, and data-driven animation to create embodied conversational agents endowed with autonomous agency, consistent values, and beliefs.

My work bridges machine learning, human–computer interaction, and computer graphics to enable AI systems such as Digital Einstein and interactive patient avatars for psychotherapy training and health education.