Black Lives Matter, Racism, and Data

By Keith Allison | November 16, 2020

representaion of visualized data in a bar graph

NYU Data Services Provides Research Resources for Analyzing and Confronting Racism

In May 2020, staff at NYU Data Services watched along with the rest of the world as protests against racism and police violence spread across the United States in the wake of the death of George Floyd. As protests continued throughout the summer, they asked themselves what they could do to contribute to this outpouring of social and political action. Much of the time it seemed overwhelming alongside the pandemic. For Michelle Thompson Gumbs, Senior Geographic Information Systems Specialist, and the Data Services team, that meant coming together via NYU Zoom to think about what sort of data they could collect that would help others analyze the situation.

“We’re a diverse team,” says Gumbs, “and not everyone has experience with US injustice because they are from elsewhere. We wanted to understand more about what was happening.” 

The first step was to come together as a team to discuss what was happening and how it was affecting individual team members. They then began the task by sharing a Google Doc where they added ideas for data that could be collected and what it might be able to provide to the NYU community. The results of this effort have been collected into a Black Lives Matter Data and Resources repository available on the Data Services website.

Jiejie Wang, a Data Services student employee studying Applied Statistics for Social Science Research at Steinhardt, was interested in using natural language processing to analyze over 60,000 Twitter posts under the hashtag #BLM from June 2020 to August 2020. These tweets covered a lot of discussion about George Floyd, Black Lives Matter, protests, 2020 political candidates, and other related issues. This process of “sentiment analysis” enabled Wang to quantitatively analyze the reaction to George Floyd’s death, visualize the progression of how positive/negative language and vocal support for political candidates changed. The data and the analysis has been made available as an R Markdown workbook.

Rebecca Levy, another Data Services student employee, built a Residential Inequality presentation using ESRI StoryMaps to create a visual representation of census and other historical data sets to “show how inherently discriminatory housing policy can and continues to contribute to systemic racism in the United States.”

Visualizing Race Identity among Second-Generation Immigrants in New York, 1999-2001 is a model lesson plan curated by NYU Journalism Librarian Katy Boss. It “integrates a dataset and sample data visualizations of a study that explore race identity among immigrants in the metro NYC area during the late 1990s and early 2000s.”

In addition, the Data Services BLM repository houses links to related data sets and lesson plans collected by NYU colleagues as well as other universities and researchers, including ProPublica’s Hate News Index, Stanford University’s Open Policing Project, and the Urban Art Mapping George Floyd and Anti-Racist Street Art database, among many others.

Collection and visual rendering of data is an important part of studying racism and race relations, though of course data can only tell part of the story. NYU Data Services hopes that the evolving curation of this data will spark meaningful, if at times difficult, classroom discussion and research related to these most important topics. All presentations and data sets are publicly available, and Data Services staff are available to explore how the data can be incorporated into classwork and research. Assembling the information “has helped a lot of us to grow our own knowledge” says Gumbs, and she and the rest of the team hope it can do the same at NYU and beyond.