An Epidemiology of Information: Data Mining the 1918 Influenza Pandemic

This project seeks to harness the power of data mining techniques with the interpretive analytics of the humanities and social sciences to understand how newspapers shaped public opinion and represented authoritative knowledge during this deadly pandemic. This project makes use of the more than 100 newspaper titles for 1918 available from Chronicling America at the United States Library of Congress and the Peel’s Prairie Provinces collection at the University of Alberta Library. The application of algorithmic techniques enables the domain expert to systematically explore a broad repository of data and identify qualitative features of the pandemic in the small scale as well as the genealogy of information flow in the large scale. This research can provide methods for understanding the spread of information and the flow of disease in other societies facing the threat of pandemics.

Principal Investigators

Edward T. Ewing, Virginia Polytechnic Institute & State University, US, NEH
Bernice L. Hausman, Virginia Polytechnic Institute & State University, US, NEH
Bruce Pencek, Virginia Polytechnic Institute & State University, US, NEH
Narendran Ramakrishnan, Virginia Polytechnic Institute & State University, US, NEH
Gunther Eysenbach, University of Toronto, CAN, SSHRC