Bitter Data transforms 100,000 distress postings from Chinese social media into a multi-sensory experience using data edibilization. We’ve mapped distress data quantity to the bitterness and color of tea through data analysis and experimentation.

Participants taste, smell, and observe 11 cups of tea, each embodying a year’s distress data, in our workshop. Their facial expressions, recorded upon tasting, visually indicate emotional states. This project explores benefits and pragmatic solutions to challenges of data edibilization.

This is the second phase of the Trouble Overload. In the first phase, the expression of trouble data overshadowed the emotions of the individuals that make up the big data, creating a sense of detachment and objectivity that distanced the audience from the work. In this phase, taste and color are introduced to allow the audience to personally experience the bitterness embedded in the data.