The Pervasive Presence of Chinese Government Content on Douyin Trending Videos

All Abstracts > The Pervasive Presence of Chinese Government Content on Douyin Trending Videos

The Pervasive Presence of Chinese Government Content on Douyin Trending Videos

Authors | Affiliation:
Yingdan Lu | Stanford University; Jennifer Pan | Stanford University

Presenting at:
2B | China’s digital communication industry and its discontent


Abstract:

The proliferation of social media has expanded the strategies for government propaganda, but quantitative analyses of the content of digital propaganda continue to rely predominantly on textual data. In this paper, we use a multi-modal approach that combines analysis of video, text, and meta-data to explore the characteristics of Chinese government activities on Douyin, China’s leading social video-sharing platform. We apply this multi-modal approach on a novel dataset of 50,813 videos we collected from the Douyin Trending page. We find that videos from the Douyin accounts of Chinese state media, government, and Communist Party entities (what we call state-affiliated accounts) represent roughly half of all videos featured on the Douyin Trending page. Videos from state-affiliated accounts focus on political information and news while other Trending videos are dominated by entertainment content. Videos from state-affiliated accounts also exhibit features, including short duration, brightness, and high entropy, found in prior research to increase attention and engagement. However, videos from state-affiliated accounts tend to exhibit lower average levels of audience engagement than Trending videos from other types of accounts. The methods and substantive findings of this paper contributes to an emerging literature in communication on the computational analysis of video as data.


About the authors

Yingdan Lu

Email: yingdan@stanford.edu

Yingdan Lu is a Ph.D. Candidate in the Department of Communication at Stanford University. Her research focuses on new media, political communication, and information manipulation in authoritarian regimes. Methodologically, she examines massive textual data from social media and millions of moment-by-moment screenshots collected from mobile users. Prior to her doctoral study, she received her M.A. degree from Center for East Asian Studies, Stanford University, and B.A. degree from School of Journalism and Communication, Tsinghua University.

Jennifer Pan

Email: –

Jennifer Pan is an Assistant Professor of Communication, and an Assistant Professor, by courtesy, of Political Science and Sociology at Stanford University. Her research sides at the intersection of political communication and comparative politics. Her work has appeared in peer reviewed publications such as the American Political Science Review, American Journal of Political Science, Journal of Politics, and Science.

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