Investigating medical YouTubers’ parasocial visual cues in their COVID-related videos: a computer vision approach

This study explores the relationship between parasocial visual cues and user engagement with medical YouTubers’ COVID-19-related videos, using a novel approach with computer vision. Based on prior literature, we measured parasocial visual cues through bodily address—where the YouTuber is seen speaking to the audience—and camera gaze—where the YouTuber is looking at the camera. For user engagement, we recorded the numbers of likes and comments, which respectively reflect viewers’ support and engagement with the discussions raised by the YouTubers. Our linear regression analyses revealed contrasting findings: bodily address was positively associated with both the number of likes and comments, whereas camera gaze was not significantly associated with either. In other words, medical YouTubers’ presence in their videos could significantly increase both the number of likes and comments, whereas their camera gaze may have little to do with viewer engagement. Our findings on bodily address align with previous parasocial interaction studies conducted through manual analysis. However, our findings on camera gaze correspond only with literature specific to parasocial interactions on YouTube and diverge from broader arguments in the general parasocial interaction literature. The possible rationales behind these contrasting results are discussed from both theoretical and practical perspectives.