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Article Dans Une Revue Acta Polytechnica Hungarica Année : 2022

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

Anna Esposito
  • Fonction : Auteur
Terry Amorese
  • Fonction : Auteur
Michele Buonanno
  • Fonction : Auteur
Marialucia Cuciniello
  • Fonction : Auteur
Antonietta Esposito
  • Fonction : Auteur
Marcos Faundez-Zanuy
  • Fonction : Auteur
Maria Teresa Riviello
  • Fonction : Auteur
Carmine Spagnuolo
  • Fonction : Auteur
Alda Troncone
  • Fonction : Auteur
Gennaro Cordasco
  • Fonction : Auteur

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.

Dates et versions

hal-04277391 , version 1 (09-11-2023)

Identifiants

Citer

Anna Esposito, Terry Amorese, Michele Buonanno, Marialucia Cuciniello, Antonietta Esposito, et al.. Handwriting and Drawing Features for Detecting Personality Traits: An Analysis on Big Five Sub-dimensions. Acta Polytechnica Hungarica, 2022, 19 (11), pp.65-84. ⟨10.12700/APH.19.11.2022.11.4⟩. ⟨hal-04277391⟩
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