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Countermeasures for Enhancing User-Generated Content on Short Video Platforms Through Recommendation Mechanisms
- 1 City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong
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Abstract
The proliferation of short video applications and platforms has paralleled the growing popularity of this media format. In the increasingly competitive landscape of short-form video, companies have adopted numerous strategies to expand their market share, retain active users, and ensure sustainable platform operations. Among these strategies, one of the most pivotal is the utilization of recommendation mechanisms and algorithms to personalize video suggestions for users. For platform users, the additional traffic and exposure facilitated by recommendation mechanisms present a valuable opportunity for their videos to reach a wider audience. This paper delves into the characteristics and commonalities of user-generated content on video platforms influenced by recommendation algorithms, and examines the strategies employed by video creators to harness the increased traffic and exposure provided by these mechanisms, as well as the dynamics between users and the platform. We have randomly selected video data from the "Beeping Beeping" pop-up website for analysis. The study also scrutinizes the actions taken by video producers to exploit the resources and opportunities provided by the recommendation mechanism. Furthermore, it explores the interactions between users and the platform. To carry out this research, we selected a sample of twenty random videos from each of the ten video producers who boast a substantial fan base on the "Bleeping.com" website. While the recommendation mechanism simplifies the user experience, it simultaneously offers varying resources and opportunities to different users. Users who comprehend the platform's recommendation guidelines and underlying algorithms can proactively leverage the mechanism to aid in video creation and dissemination. This approach enables them to actively promote high-quality user-generated content on the video platform during the video creation and upload phases.
Keywords
short video, recommendation, algorithm, personalized recommendation, user-generated content
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Cite this article
Mingxin,X. (2024). Countermeasures for Enhancing User-Generated Content on Short Video Platforms Through Recommendation Mechanisms. Advances in Economics, Management and Political Sciences,73,45-60.
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The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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