Universität zu Köln

Gloor, Peter A., Fronzetti Colladon, Andrea ORCID: 0000-0002-5348-9722, Altuntas, Erkin, Cetinkaya, Cengiz, Kaiser, Maximilian F., Ripperger, Lukas and Schaefer, Tim (2022). Your Face Mirrors Your Deepest Beliefs-Predicting Personality and Morals through Facial Emotion Recognition. Future Internet, 14 (1). BASEL: MDPI. ISSN 1999-5903

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Abstract

Can we really read the mind in the eyes? Moreover, can AI assist us in this task? This paper answers these two questions by introducing a machine learning system that predicts personality characteristics of individuals on the basis of their face. It does so by tracking the emotional response of the individual's face through facial emotion recognition (FER) while watching a series of 15 short videos of different genres. To calibrate the system, we invited 85 people to watch the videos, while their emotional responses were analyzed through their facial expression. At the same time, these individuals also took four well-validated surveys of personality characteristics and moral values: the revised NEO FFI personality inventory, the Haidt moral foundations test, the Schwartz personal value system, and the domain-specific risk-taking scale (DOSPERT). We found that personality characteristics and moral values of an individual can be predicted through their emotional response to the videos as shown in their face, with an accuracy of up to 86% using gradient-boosted trees. We also found that different personality characteristics are better predicted by different videos, in other words, there is no single video that will provide accurate predictions for all personality characteristics, but it is the response to the mix of different videos that allows for accurate prediction.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Gloor, Peter A. UNSPECIFIED UNSPECIFIED UNSPECIFIED Fronzetti Colladon, Andrea UNSPECIFIED orcid.org/0000-0002-5348-9722 UNSPECIFIED Altuntas, Erkin UNSPECIFIED UNSPECIFIED UNSPECIFIED Cetinkaya, Cengiz UNSPECIFIED UNSPECIFIED UNSPECIFIED Kaiser, Maximilian F. UNSPECIFIED UNSPECIFIED UNSPECIFIED Ripperger, Lukas UNSPECIFIED UNSPECIFIED UNSPECIFIED Schaefer, Tim UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-678549
DOI:	10.3390/fi14010005
Journal or Publication Title:	Future Internet
Volume:	14
Number:	1
Date:	2022
Publisher:	MDPI
Place of Publication:	BASEL
ISSN:	1999-5903
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language EXPRESSION; VALUES Multiple languages Computer Science, Information Systems Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/67854