Dynamic Advertising Insertion Strategy with Moment-to-Moment Data Using Sentiment Analysis: The Case of Danmaku Video


Zhi Li
Shen Duan
Rui Li


Online video platforms realize that increased user engagement increases advertising revenue. For this reason, the danmaku live chat function, which allows users to chat in real-time while watching videos, is developed. Based on Stimuli-Organisms-Response (SOR) theory, this study proposes a new approach—an effective user-targeted method for danmaku video advertising insertion strategy. Specifically, by using moment-to-moment danmaku data and listening to users’ live comments, this study examines the influence of the feature variables of video advertisement groups on users’ behavior and emotion. Empirical results show that the repeat times of platform advertisement, the exposure duration of a video advertisement group, the number of advertisements, and the number of brands impact users’ danmaku behavior. The findings imply that enhanced content-based interactions contribute to video advertising success.

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August, 2022

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