Points of Light explores street protest in the United States from January 2017 through October 2019. The project shows how protests rise and fall in response to current events, the importance of organizing, and the topics that inspired protest in different places. Through stories about guns, the environment, immigration, education, and more, Points of Light argues that protest does not belong to coastal cities or liberal causes. Rather, protest is a tool that all Americans can use to push for change.
The project uses protest data from Count Love. I created the visuals independently as a personal and class project.
Points of Light helped to bring attention to the incredible work done by Tommy Leung and Nathan Perkins at Count Love. The project was featured in AnyChart’s DataViz Weekly alongside stories by Bloomberg, the New York Times, and Reuters. The project was also featured in Warning: Graphic Content and David Napoli’s newsletter. Points of Light inspired a series on Spreadsheet Journalism, considering the pros and cons of recreating the project in Excel. The project will also be discussed on an upcoming episode of the Data Viz Today podcast, and a chart from the project will be included in Jon Schwabish’s upcoming book, Better Data Visualizations.
I used R to analyze the data and create preliminary graphics. Andrew Ba Tran’s muckrakr package was invaluable for working with the Count Love data, and I used ggplot to create the rough visualizations. The only exception was the streamgraph, which I created in RawGraphs. I polished and annotated the static graphics in Illustrator. I created the interactive graphics with D3.js. This was my first D3 project, and I found Amelia Wattenberger’s Fullstack D3 and Data Visualization incredibly helpful. I wrote more about the creation of the project at my blog, Data and Dragons.
What was the hardest part of this project?
There were two main challenges in this project. The first was balancing my own curiosity with providing interesting, relevant information to the reader. There were many avenues of analyis that, while interesting to me, would have required too much work from the reader for too little return.
The second (and most difficult) challenge was learning to do mundane work about intense topics. It felt wrong to focus on caption alignment and font size when writing about mass shootings and human rights violations. However, making that information accessible is part of honoring the victims. I had to learn that patient, steady, un-dramatic effort is the best thing I can do, even in the face of very dramatic feelings.
What can others learn from this project?
I hope that the site itself helps readers to understand that protest doesn’t just happen: it requires organization and commitment. I also hope that readers walk away understanding that protest isn’t always effective, it isn’t futile either. While protests about guns didn’t lead to lasting policy change, healthcare and education protests made a material difference in U.S. law and West Virginia labor conditions.
From my making-of posts, I hope that others learn that figuring out new technologies and datasets is possible, even if they seem insurmountable at first glance. I also hope that I can pass on the data profiling process I learned at the University of Virginia to others.