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Personality traits prediction based on eye movements while reading manga.

Yuichi Wada1

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Eye movements during manga reading can predict extraversion, a key personality trait. This study explored gaze behaviors for personality detection, finding fixation rate and pupillary response informative.

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Area of Science:

  • Psychology
  • Computer Science
  • Human-Computer Interaction

Background:

  • Machine learning models can predict personal traits from real-world eye movement data.
  • Previous studies analyzed gaze during campus navigation and social media browsing.

Purpose of the Study:

  • To investigate if eye movements during manga reading can predict personality traits.
  • To extend previous findings to a new type of visual engagement: reading Japanese comics (manga).

Main Methods:

  • Recorded eye movements of 51 participants reading manga.
  • Trained machine learning classifiers to predict Big Five personality traits from eye movement features.
  • Utilized SHapley Additive exPlanation (SHAP) for model interpretation.

Main Results:

  • Only extraversion was predictable among the Big Five traits.
  • The best model achieved a macro F1 score of 0.49, comparable to prior research.
  • High fixation rate, pupillary response, and blink rate were identified as key predictive features.

Conclusions:

  • Gaze behaviors during manga reading partially replicate associations between eye movement and personality.
  • Manga reading provides informative gaze data for detecting an individual's extraversion.
  • Potential advantages of using manga for gaze-based personality detection were highlighted.