Recognition of extraversion level based on handwriting and support vector machines.
This study investigated whether it is possible to train a machine to discriminate levels of extraversion based on handwriting variables. Support vector machines (SVMs) were used as a learning algorithm. Handwriting of 883 people (404 men, 479 women) was examined. Extraversion was measured using the Polish version of the NEO-Five Factor Inventory. The handwriting samples were described by 48 variables. The support vector machines were separately trained and tested for each sex, using 10-fold cross-validation. Good recognition accuracy (around .7) was achieved for 10 handwriting variables, different for men and women. The results suggest the existence of a relationship between handwriting elements and extraversion.
Institute of Psychology, Cardinal Stefan Wyszynski University, Warsaw, Poland. z.gorska@uksw.edu.pl
Zuzanna
Z
Górska
Artur
A
Janicki
D000328:Adult; D005120:Extraversion, Psychological; D005260:Female; D006236:Handwriting; D006801:Humans; D008297:Male; D010552:Personality Assessment; D011044:Poland; D015203:Reproducibility of Results; D012727:Sex Characteristics; D060388:Support Vector Machine