Research On The Influence Of The Quantity Of Bullet-Screen Comments On Users’ Video-liking Intention

In recent years,Bullet-Screen Comments(BSCs)have become increasingly popular in various online consumption scenarios,such as online video websites,live streaming platforms,which has also sparked widespread discussion and research in the academic community.Many studies have investigated the impact of BSCs on user experience.Unlike these studies,this article takes a more comprehensive approach,exploring the changes on video liking intention during the process of BSCs quantity going from zero to one and from a few to a lot.In addition,this article introduces social presence,information overload as mediator variables and BSCs usage frequency as a moderating variable to better analyze the impact of BSCs on video liking intention.This study examines the impact of BSCs presence and BSCs quantity on viewers liking of an online video.Using five experimental studies,the current research shows that the relationship between BSCs quantity and video-liking intention generally shows an inverted U-shape.Specifically,when participants watch a video with BSCs,they have greater social presence and are more willing to like the video.However,subsequent studies have shown that a large(vs.small)quantity of BSCs would decrease consumers’ liking intention of the video.This study also uncovers that the negative effect of BSCs quantity on video-liking is mediated by perceived information overload: a large amount of BSCs increases the informational cognitive load of viewers,decreases video-viewing experience,and subsequently leads to reduced video-liking.This study further demonstrates a moderating role of viewers’ BSCs usage level on the impact of BSCs quantity on video-liking: the negative effect of large-quantity BSCs on video-liking remains significant for light BSCs users,but is reduced to non-significant for heavy BSCs users.The above results have contributed to the theory of BSCs and information overload,and provide feasible suggestions for online video platforms,online live streaming platforms,etc.from two aspects: the number of BSCs and the frequency of user BSCs usage.