Emotion Detection in International Students Using a Social Robot
Year: 2024
Type: conference-paper
Abstract: With growing concerns about the mental health of international students, driven by increased loneliness and communication barriers in foreign environments, this study sought to evaluate the effectiveness of emotion detection using the social robot Furhat. The research compared the experiences of international students with Dutch students to better understand the role of emotional detection in both groups. Two models were tested: a facial detection model and a gesture detection model, to assess their accuracy in recognizing emotions. The results showed that the facial detection model outperformed the gesture detection model in terms of accuracy. However, when emotional states in the gesture model were combined, its accuracy improved, bringing it closer to the performance of the facial detection model. No significant differences were found in the emotional responses of international and Dutch students. Additionally, participants from both groups exhibited positive attitudes toward the robot, indicating general acceptance and comfort with interacting with Furhat. These findings suggest that social robots could play a role in supporting the emotional well-being of international students and provide directions for future research.
Authors: Sam Leewis, John van Meerten, Koen Smit, Ha Bui
Institution: University of Applied Sciences Utrecht
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4408967644