Eye movements during everyday behavior predict personality traits

Sabrina Hoppe, Tobias Loetscher, Stephanie Morey, Andreas Bulling

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    105 Citations (Scopus)
    20 Downloads (Pure)


    Besides allowing us to perceive our surroundings, eye movements are also a window into our mind and a rich source of information on who we are, how we feel, and what we do. Here we show that eye movements during an everyday task predict aspects of our personality. We tracked eye movements of 42 participants while they ran an errand on a university campus and subsequently assessed their personality traits using well-established questionnaires. Using a state-of-the-art machine learning method and a rich set of features encoding different eye movement characteristics, we were able to reliably predict four of the Big Five personality traits (neuroticism, extraversion, agreeableness, conscientiousness) as well as perceptual curiosity only from eye movements. Further analysis revealed new relations between previously neglected eye movement characteristics and personality. Our findings demonstrate a considerable influence of personality on everyday eye movement control, thereby complementing earlier studies in laboratory settings. Improving automatic recognition and interpretation of human social signals is an important endeavor, enabling innovative design of human-computer systems capable of sensing spontaneous natural user behavior to facilitate efficient interaction and personalization.

    Original languageEnglish
    Article number105
    Number of pages8
    JournalFrontiers in Human Neuroscience
    Publication statusPublished - 13 Apr 2018


    • Eye tracking
    • Eye-based user modeling
    • Gaze behavior
    • Machine learning
    • Personality
    • Real world


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