Analysis on the “Douyin (Tiktok) Mania” Phenomenon Based on Recommendation Algorithms

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 algori...

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Bibliographic Details
Published inE3S web of conferences Vol. 235; p. 3029
Main Author Zhao, Zhengwei
Format Journal Article Conference Proceeding
LanguageEnglish
Published Les Ulis EDP Sciences 01.01.2021
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Summary: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.
Bibliography:ObjectType-Conference Proceeding-1
SourceType-Conference Papers & Proceedings-1
content type line 21
ISSN:2267-1242
2555-0403
2267-1242
DOI:10.1051/e3sconf/202123503029