Multiagent Social Influence Detection Based on Facial Emotion Recognition
There has been an increasing interest in information diffusion within social networks and the usage of multiagent systems for knowledge discovery. In this paper, we build a multiagent system that can track the social correlations within a group of people based on video data. Our information diffusion system targets small groups of people, possibly composed of office workers, meeting attendees, etc. Adopting a multiagent architecture to study the influential correlations in a social network is an adequate choice since it maintains the scalability and robustness of the system. The correlation amongst the nodes of the social network is built on the basis of facial emotions. We evaluated the method in a social network with scripted discussions. Our results show that the emotion propagation was effectively reflected in the predicted social influence correlation.
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