The design of social media encourages a highly unequal distribution of attention: Some content creators and some posts are viewed by millions, while others remain obscure. Virality has effects both good and bad. A movement protesting against injustice may go viral and be able to build power. At the same time, misinformation might also go viral.
There are many academic papers on viral information cascades, but we can understand virality better if we also get an intuitive feel for it. This interactive visualization helps us do just that. It’s a collaboration between the Knight Institute and the Brown Institute for Media Innovation. The authors, Samia Menon and Sahil Patel, found ingenious ways to work around the limitations of Twitter’s API to reconstruct the information cascades of a few highly popular tweets. Through this visualization you can see—and perhaps feel—how the engagement events on those tweets unfolded over time. You will also be able to visualize the effect of demotion: a content moderation strategy where content is not taken down but its reach is algorithmically decreased.
Click the image below to experience the visualization.
This project was built in collaboration with the Brown Institute for Media Innovation.
Arvind Narayanan is the Knight Institute visiting senior research scientist for 2022-2023.