Meanwhile In China

Multimedia installation in collaboration with Matthias Pitscher | 2019






Sai Bao & Yang Mu (Sofia Braga & Matthias Pitscher) create art within and out of digital social networks. Through subversive interactions they critically engage in a conversation with big centralized online platforms. Using content creators as their paint and code, performance and video as their paintbrush they reappropriate digital life. “When you have so much content out there already, why bother to produce new stuff?”


Douyin, internationally known as TikTok, became one of the most successful apps worldwide. China alone accounts for 150 million active users and over 1 Billion smartphones worldwide have installed the application. In our work we are exploring this vast digital ecosystem from different perspectives. By capturing the interface we are preserving a moment in an incredibly fast changing environment. Douyin’s AI recommendation algorithm generates a list of videos that is optimized for your engagement. We decontextualize those found images without alteration to give visitors the space to reflect upon them. Using the app from different locations, in different times and with different accounts we hope to gain insight into the mechanism of the platform and understand the users within.

The work explores the chinese social network Douyin from different perspective. The app is an exact clone of internationally known TikTok, but the content is highly censored. If you search for terms like „reeducation camps“ you will get blocked from using the search function at all. The video installation, running an 8 hour loop, shows entertaining content next to chinese propaganda against for example the Hong Kong protesters. Search terms like Donald Trump result in videos that do not show the american president themself, indicating facial recognition being used for censorship. The wall behind the TV is covered with a collage of graphs and datapoints found online showcasing the exploding growth and user distribution on the platform. The graphs themselves are stripped of any labelling, making them unreadable in a common sense.