User Mood Detection in a Social Network Messenger Based on Facial Cues

Payam Jome Yazdian, Hadi Moradi

Abstract: In this paper, we propose a mood detection approach which is crucial for human-computer and human-human interaction. In the proposed method, the facial emotional changes are observed through a camera while users use a social network messenger. The advantage of this approach, over the previously proposed approaches, is in its natural setup in which people facially express their feelings, while they read and interact in the social network. This setup eliminates the need for artificial stimulus since social networks are normally filled with different stimulus. The proposed approach is implemented on the Telegram social media messenger. The results show good performance in determining the mood of users. A very promising usage of the proposed approach is in helping human-human relation by providing the mood of one person to another person before an encounter.