The Chronicle of Higher Education (February 27, 2015) contains an article by Jennifer Howard on the Spanish Flu Project: a big data project funded by the NEH (among other entities) exploring reporting on the 1918 Spanish Flu. As Howard describes the research:
The team began with several questions: How did reporting on the Spanish flu spread in 1918? And how big a role did one influential person play in shaping how the outbreak was handled? . . . Royal S. Copeland was the health commissioner of New York City in August 1918, when a ship arrived in New York Harbor from Europe with flu victims aboard . . . . Copeland helped set the tone for how the nation reacted to a viral threat—and has been the subject of debate among historians ever since, with competing camps arguing about whether he did enough.
Researchers would typically scour public statements by Copeland to answer these questions. But since the outbreak was “well documented in the popular press of the day,” it seemed an ideal topic for “digitally enabled scholarship.”
Using the Library of Congress’s Chronicling America database of historical newspapers, the HathiTrust Digital Library, and other sources, the Virginia Tech researchers sought out direct and indirect evidence of Copeland’s role: mentions and quotations, references to flu-containment strategies he promoted. “You can see his influence even if his name’s not used,” Mr. Ewing says.
The article does a good job highlighting the strengths and weaknesses of this form of digital scholarship. As Howard notes, this complex project requires both “code and context”:
To produce useful results, this kind of investigation depends on customized algorithms. But coming up with a good algorithm involves both code and context, a mingling of the complementary strengths of computer scientists and humanists . . . . The hybrid, trial-and-error nature of the Spanish-flu investigation may say something about the current state of computer-assisted humanities work. Mr. Bobley of the NEH says he has been impressed with the flu researchers’ “candid thoughts on how computational approaches like data mining are no magic bullet,” even as they expand what humanists can do. The work is a reminder, he says, that “historical documents like newspapers are rich, messy, nuanced, and complex documents that defy easy computational analysis.”