The Pervasive Presence of Chinese Government Content on Douyin Trending Videos

Yingdan Lu, Jennifer Pan

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

As audiences have moved to digital media, so too have governments around the world. While previous research has focused on how authoritarian regimes employ strategies such as the use of fabricated accounts and content to boost their reach, this paper reveals two dif ferent tactics the Chinese government uses on Douyin, the Chinese version of the video-sharing platform TikTok, to compete for audience attention. We use a multi-modal approach that combines analysis of video, text, and meta-data to examine a novel dataset of Douyin videos. We f ind that a large share of trending videos are produced by accounts af f iliated with the Chinese government. These videos contain visual characteristics designed to maximize attention such as high levels of brightness and entropy and very short duration, and are more visually similar to content produced by celebrities and ordinary users than to content from non-of f icial media accounts. We also f ind that the majority of videos produced by regime-af f iliated accounts do not f it traditional def initions of propaganda but rather contain stories and topics unrelated to any aspect of the government, the Chinese Communist Party, policies, or politics.

Original languageEnglish (US)
Pages (from-to)68-97
Number of pages30
JournalComputational Communication Research
Volume4
Issue number1
DOIs
StatePublished - 2022

Funding

Our thanks to Xin Jin, Yitian Liu, Yuyang Shi, and Yiwei Wang for research assistance; Ben Lee, Haoran Li, Yansong Tang, and participants of the Chinese Political Communication Forum and SICSS-Beijing for many helpful comments and suggestions; and to the National Science Foundation (Grant #1831481) and the Stanford Graduate Fellowship for research support.

Keywords

  • China
  • Computer Vision
  • Douyin
  • Tiktok
  • Video
  • political communication

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Linguistics and Language

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