학술논문

Computational Study of Primitive Emotional Contagion in Dyadic Interactions
Document Type
Periodical
Source
IEEE Transactions on Affective Computing IEEE Trans. Affective Comput. Affective Computing, IEEE Transactions on. 11(2):258-271 Jun, 2020
Subject
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Computational modeling
Mathematical model
Atmospheric measurements
Particle measurements
Synchronization
Psychology
Primitive emotional contagion
facial expressions analysis
sentiment analysis
cross-recurrence quantification analysis
Language
ISSN
1949-3045
2371-9850
Abstract
Interpersonal human-human interaction is a dynamical exchange and coordination of social signals, feelings and emotions usually performed through and across multiple modalities such as facial expressions, gestures, and language. Developing machines able to engage humans in rich and natural interpersonal interactions requires capturing such dynamics. This paper addresses primitive emotional contagion during dyadic interactions in which roles are prefixed. Primitive emotional contagion was defined as the tendency people have to automatically mimic and synchronize their multimodal behavior during interactions and, consequently, to emotionally converge. To capture emotional contagion, a cross-recurrence based methodology that explicitly integrates short and long-term temporal dynamics through the analysis of both facial expressions and sentiment was developed. This approach is employed to assess emotional contagion at unimodal, multimodal and cross-modal levels and is evaluated on the Solid SAL-SEMAINE corpus. Interestingly, the approach is able to show the importance of the adoption of cross-modal strategies for addressing emotional contagion.