Inference of personality traits and affect schedule by analysis of spontaneous reactions to affective videos

This paper presents a method for inferring the Positive and Negative Affect Schedule (PANAS) and the BigFive personality traits of 35 participants through the analysis of their implicit responses to 16 emotional videos. The employed modalities to record the implicit responses are (i) EEG, (ii) peripheral physiological signals (ECG, GSR), and (iii) facial landmark trajectories. The predictions of personality traits/PANAS are done using linear regression models that are trained independently on each modality. The main findings of this study are that: (i) PANAS and personality traits of individuals can be predicted based on the users' implicit responses to affective video content, (ii) ECG+GSR signals yield 70%±8% F1-score on the distinction between extroverts/introverts, (iii) EEG signals yield 69%±6% F1-score on the distinction between creative/non creative people, and finally (iv) for the prediction of agreeableness, emotional stability, and baseline affective states we achieved significantly higher than chance-level results.