Abstract
As one of the most popular short video platform, Douyin has accumulated more than half of the Chinese netizens as its daily active users. Many users spend plenty of time viewing Douyin short videos, which make Douyin addiction become a widespread phenomenon. In this paper, the author analyzes algorithm principles used in Douyin. Combining both perspectives of mass media communication and algorithm technology to explain how it effects Douyin addiction. For one thing, the recommendation algorithm caters users by fully meeting their needs. Using the hierarchical interest label tree, the user persona and the partitioned data buckets strategy to recommend more accurate and personalized contents. For another, the algorithm uses the collaborative filtering algorithm and low-cost interaction design mechanism to make traps for users. The author also finds that there is a closed-loop relationship between Douyin addiction and algorithm optimization. The algorithm principles positively effects users’ continuance intention. Meanwhile, the more frequent the user uses Douyin, the more accurate the algorithm will be. If not intervened, the addiction may be severely exacerbated. So, the author comes up with a few suggestions for Douyin developers and users, trying to break the closed-loop.
Highlights
The Chinese origin version of TikTok, is an online short video mobile application that has been launched by ByteDance in September 2016
This research can be useful for media scholars to have a deeper understanding of the recommendation algorithm principles, and make technology and media better integrate and benefit people's lives
Through the analysis of the previous section, it is indicated that the recommendation algorithm principles, more or less, positively effects the user's addiction to Douyin
Summary
The Chinese origin version of TikTok, is an online short video mobile application that has been launched by ByteDance in September 2016 According to their official introduction, “Douyin is a short video platform that helps users express themselves and record a good life” [1]. According to Mary Meeker’s 2019 Internet Trends Report [2], which was one of the most highly anticipated annual reports for all the Internet related industries It showed that Chinese Internet robust usage growth is primarily driven by Short-Form Video. The user passively accepts the system's personalized recommendation content without any initiative selection or search This is a huge revolution to the way people are used to obtaining information on the Internet. This research can be useful for media scholars to have a deeper understanding of the recommendation algorithm principles, and make technology and media better integrate and benefit people's lives
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