The Virality of Racial Terror

We are pleased to announce today that the Mellon Foundation has funded a collaboration between the Viral Texts project and the Racial Violence Archive, “The Virality of Racial Terror in US Newspapers, 1863-1921.” VRT will employ text-mining methods to trace the circulation of reports about anti-Black violence in US newspapers in the late nineteenth and early twentieth centuries and develop a series of exhibits demonstrating how such reporting fueled both subsequent violence and acts of resistance.

We are excited about this collaboration, which will bring together the Viral Texts team’s expertise in nineteenth-century newspapers and computational methods together with the Racial Violence Archives team’s expertise in the histories and legacies of racialized violence and their reparative implications, and use this combined expertise to study a history still resonating loudly in our present.

Below we copy the first section of our grant narrative, to give a sense of what we will work on in the next three years. In addition, see this press release from the University of Illinois Urbana-Champaign’s School of Information Sciences.

Reason for the Work

In her call for Truth and Reconciliation, legal scholar and NAACP Legal Defense Fund director Sherilynn Ifill notes the complicity of newspapers and their need to atone for roles in encouraging, advertising, and otherwise aiding the perpetration of lynching.¹ Responding to this call, The Virality of Racial Terror in US Newspapers, 1863-1921 (VRT) project draws on partners’ expertise from the Viral Texts Project, at Northeastern University and the University of Illinois, and the Racial Violence Archive, at Washington University, to trace the the circulation of reports about anti-Black violence in US newspapers in the nineteenth and early twentieth centuries. VRT will investigate how:

• racial violence was recontextualized for specific regional, political, or trade readers through editor’s choices while selecting and revising stories;
• reporting of racial violence correlated to racist content in other newspaper genres (e.g., popular science, humor, poetry);
• derogatory and anti-Black content drew upon and forged white supremacist networks;
• news about racial violence correlated with the spread of new racial terror events; and
• discussion of racial violence diverged in the Black and white press.

In VRT, we will study how newspapers helped structure racial socialization by, for example, rallying support for Jim Crow laws and enhanced policing among white readers, while at the same time counter-reporting in Black papers sought to prompt anti-racist interventions. While the project’s primary focus will be historical, VRT will offer vital context to the spread of white supremacist ideologies in contemporary viral media, such as Twitter, Facebook, and Reddit, and insights into how it can be contested. We submitted our initial concept paper only days after a white surpremacist terrorist live-streamed his massacre of Black Americans in a Buffalo supermarket, seeking to spark a cascade of racial violence. Such attempts to spur “copy cat” violence through social media in 2022 mirror the dynamics of racial terror that VRT will trace in the late nineteenth and early-twentieth centuries.

In VRT, we will extend work by the Racial Violence Archive to document and map the propagation of violent events by tracing granular discourse through large-scale collections of digitized newspapers. VRT will draw on the Viral Texts Project’s computational methods for reprint identification to trace how specific stories spread around the country; the ways they were edited for specific local, racial, or political audiences; and the emergence of new texts written and circulated in response. This research will map a key element of “the wake” of racial terror recognized in important humanities research by scholars such as Saidiya Hartman and Christina Sharpe, concerning legacies of slavery and racial terror in cultural materials. In addition, we will contribute to research in computer science that seeks to understand information diffusion in noisy and partial data.