Institute of Psychology, Cardinal Stefan Wyszynski University, Warsaw, Poland.
Percept Mot Skills. 2012 Jun;114(3):857-69. doi: 10.2466/03.09.28.PMS.114.3.857-869.
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.
本研究旨在探讨是否可以通过笔迹变量训练机器来区分外向程度。支持向量机（SVM）被用作学习算法。研究人员对 883 人的笔迹（404 名男性，479 名女性）进行了检查。外向性使用波兰版的 NEO-五因素人格量表进行测量。笔迹样本由 48 个变量描述。支持向量机分别针对男性和女性进行了 10 折交叉验证的训练和测试。对于 10 个不同的男女笔迹变量，识别准确率达到了较好的水平（约为 70%）。研究结果表明，笔迹元素与外向性之间存在一定的关系。
