Reaction视频中用户弹幕信息交互行为的情感反应生成机理研究

Investigating the generation mechanism of affective response of danmaku commenting behavior in reaction videos can provide valuable insights into the reasons for affective generations and the process of affective change. This paper takes reaction videos of the Bilibili video website as examples. We conduct coding using the directed content analysis method by selecting the danmaku resources, video content, and reactor responses of 11 popular videos in different camps as samples. Based on the Affective Response Model (ARM), this paper builds a theoretical framework of the generation mechanism of affective responses of user danmaku commenting behavior in reaction videos. The results suggest that affective responses of user danmaku commenting behavior in reaction videos generally follows the path of "information cues-affective response", that is, information cues can arouse emotions or particular affective responses autonomously, and they can also affect the generation of emotions or learned affective responses by arousing particular affective responses. The proposed framework helps to improve the contextualized exploration of ARM theory in computer-mediated communication and will also provide practical implications for optimizing user-information interaction in social media.