Predicting the Big Five personality traits from handwriting

We propose the first non-invasive three-layer architecture in literature based on neural networks that aims to determine the Big Five personality traits of an individual by analyzing offline handwriting. We also present the first database in literature that links the Big Five personality type with t...

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Bibliographic Details
Published in:EURASIP journal on image and video processing 2018-07, Vol.2018 (1), p.1-17, Article 57
Main Authors: Gavrilescu, Mihai, Vizireanu, Nicolae
Format: Article
Language:English
Subjects:
Accuracy
Applications of Visual Analysis of Human Behaviour
Architecture
Biometrics
Engineering
Feature classification
Handwriting
Handwriting analysis
Image Processing and Computer Vision
Neural networks
Pattern Recognition
Personality
Personality classification
Personality traits
Predictions
Signal,Image and Speech Processing
Texts
Training
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Summary:We propose the first non-invasive three-layer architecture in literature based on neural networks that aims to determine the Big Five personality traits of an individual by analyzing offline handwriting. We also present the first database in literature that links the Big Five personality type with the handwriting features collected from 128 subjects containing both predefined and random texts. Testing our novel architecture on this database, we show that the predefined texts add more value if enforced on writers in the training stage, offering accuracies of 84.4% in intra-subject tests and 80.5% in inter-subject tests when the random dataset is used for testing purposes, up to 7% higher than when random datasets are used in the training phase. We obtain the highest prediction accuracy for Openness to Experience, Extraversion, and Neuroticism (over 84%), while for Conscientiousness and Agreeableness, the prediction accuracy is around 77%. Overall, our approach offers the highest accuracy compared with other state-of-the-art methods and results are computed in maximum 90 s, making the approach faster than the questionnaire or psychological interviews currently used for determining the Big Five personality traits. Our research also shows there are relationships between specific handwriting features and prediction with high accuracy of specific personality traits and this can be further exploited for improving, even more, the prediction accuracy of the proposed architecture.
ISSN:1687-5281
1687-5176
1687-5281
DOI:10.1186/s13640-018-0297-3