This project seeks to understand how newspapers shaped public opinion during the 1918 influenza pandemic. Using data mining techniques combined with historical and rhetorical analysis, we explore hundreds of newspaper titles, including those from Chronicling America at the United States Library of Congress and the Peel’s Prairie Provinces collection at the University of Alberta Library, to understand the flow of information about the spread and impact of disease. For more information, contact Professor E. Thomas Ewing, Principal Investigator and Project Director, Department of History, Virginia Tech, at

Recent Submissions

  • Segmentation Algorithm 

    Gad, Samah (2014-04-09)
    We developed a dynamic temporal segmentation algorithm that wraps around topic modeling algorithms for the purpose of identifying change points where significant shifts in topics occur. The main task of the segmentation ...
  • An Epidemiology of Information: Data Mining the 1918 Influenza Epidemic Project Report 

    Hausman, Bernice L.; Pencek, Bruce; Ramakrishnan, Naren; Eysenbach, Gunther; Ewing, E. Thomas; Kerr, Kathleen; Gad, Samah (2014-04-07)
    This project research report describes the results of four case studies undertaken as part of Virginia Tech’s “An Epidemiology of Information: Data Mining the 1918 Flu Pandemic,” which was funded through the Digging into ...
  • Tone classifier 

    Gad, Samah (2014-02-24)
    The goal of tone analysis is to identify tone from text. We focused on the following tones: alarmist, warning, reassuring, and explanatory. To detect tones from text automatically, we used a supervised machine learning ...
  • 1918 Spanish Flu 

    Ewing, E. Thomas; Hausman, Bernice L.; Ramakrishnan, Naren (2013-10-02)