Research on Stakeholder Negotiation and Imitative Platform Expression of High-energy Vlogs from the Perspective of Algorithmic Visibility

To clarify the generation logic of short video homogenization driven by algorithm distribution, this article uses algorithm visibility as the analytical framework to explore the intrinsic relationship between the platform, creator, and user tripartite negotiation mechanism and the large-scale imitation production of high-energy vlogs. This paper selects TikTok, Bilibili and Xiaohongshu as research samples and carries out empirical analysis based on statistical data from China Audio-Video Association, QuestMobile and NewRank. Actual test data shows that the completion rate of high-energy emotional vlogs reaches 63.4%, which is 25.3 percentage points higher than conventional documentary vlogs. The data advantage has made this type of content the main replication template in the industry. The hierarchical traffic distribution mechanism promotes a long-term interaction among three parties: the platform regulates content development by adjusting algorithm weight parameters, creators obtain exposure by imitating existing works, and user interaction data continuously drives the iteration of recommendation models. Imitative works raise the costs of trial and error for emerging creators. The Matthew effect in traffic distribution also worsens content homogenization across vlog content segments. This paper puts forward corresponding solutions from four perspectives: algorithm optimization, vertical content creation, creator competency development and industry regulation, to drive the sound development of this segment.