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Handwriting and Drawing Features for Detecting Personality Traits: An Analysis on Big Five Sub-dimensions

  • Anna Esposito
  • , Terry Amorese
  • , Michele Buonanno
  • , Marialucia Cuciniello
  • , Antonietta M. Esposito
  • , Marcos Faundez-Zanuy
  • , Laurence Likforman-Sulem
  • , Maria Teresa Riviello
  • , Carmine Spagnuolo
  • , Alda Troncone
  • , Gennaro Cordasco
  • Department of Psichology
  • University of Campania L. Vanvitelli
  • Istituto Nazionale di Geofisica e Vulcanologia (INGV)
  • Escola Superior Politecnica
  • Université Paris-Saclay
  • Department of Computer Science
  • University of Salerno

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2 Citations (Scopus)

Résumé

Handwriting and Drawing are functional tasks involving physical and cognitive processes. Recently they have been investigated for detecting cognitive and motor disorders. In this work, handwriting/drawing features are investigated for identifying connections with personality traits. For this purpose, an experiment comprising seven handwriting/drawing tasks has been administrated to 78 young adults (mean age=24.6 ± 2.4 years) equally balanced by gender. Handwriting and Drawing activities-both on and close to the paper – had been recorded online through a digitizing tablet able to measure handwriting and drawing features such as pressure, speed, dimension, and inclination of each pen-stroke on the paper. Participants were asked to fill the Big Five Personality Questionnaire (BFQ) and according to the scores obtained for each of the 5 dimensions and 10 Big Five sub-dimensions, were partitioned into three categories: low, typical, and high. To evaluate whether the recorded handwriting/drawing features are connected with personality traits ANOVA repeated measures have been performed with gender and group category (low, typical, and high) as between and the listed handwriting/drawing features as within factors. The analyses show significant differences among low, typical and, high BFQ scores for the main Big Five dimensions and the ten Big Five sub-dimensions, indicating that personality traits can be revealed by a quantitative analysis of the proposed handwriting/drawing features.

langue originaleAnglais
Pages (de - à)65-84
Nombre de pages20
journalActa Polytechnica Hungarica
Volume19
Numéro de publication11
Les DOIs
étatPublié - 1 janv. 2022
Modification externeOui

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