An Epidemiology of Information: New Methods for Interpreting Data and Disease
Analysis
This project consisted of four case studies that used text interpretation and tone analysis. As discussed below, newspapers were shown to be a key source for information and public opinion; showing the extend of the news coverage and how reassurance and warnings were given to the public.
Within the four case studies they found the following:
Weekly Newspapers Case Study. Our review of weekly newspapers indicates that they served a far more complex function than some scholars suggest and illustrates the value of newspaper reporting beyond the mortality data extracted by epidemiological studies.
Daily Newspapers Case Study. The outputs for all the papers together significantly differ from the outputs for the individual papers. It is clear that some papers influence the output of the aggregate more than others, either due to poor data quality or larger text chunks that are analyzed algorithmically.
Vaccination-Visualization Case Study. The process of research and interpretations of data outputs are affected by various forms of visualization as well as by the data input conventions underlying the algorithms. ThemeDelta is a visualization of topic modeling and segmentation that allows the researcher to follow a specific word or word cluster across temporal segments.
Public Health Officials Case Study. These methods confirm Royal S. Copeland’s prominent role in shaping the public health response to the 1918 influenza epidemic. They also reveal that his name was closely associated with public health measures, both within New York City and nationally. Tone classification calls into question historical claims that Copeland’s language was too optimistic for the circumstances.
Samah Gad, Computer Science Graduate Research Assistant; Bernice Hausman, Co-PI; and Tom Ewing, PI, discuss network analysis.
Researchers
They were a part of the National Endowment for the Humanities (NEH) Digging Into Data Challenge, which began in 2011. The report was published April 2, 2014, this digital project was completed over a 3 year time. Researchers from Virginia Tech and University of Toronto came together and collected data from both nations relating to the influenza pandemic.
E. Thomas Ewing
Associate Dean for Research and Graduate Studies
Professor, Department of History
College of Liberal Arts and Human Sciences
Virginia Tech
Bernice L. Hausman
Professor, Department of English
Virginia Tech
Bruce Pencek
College Librarian for Social Sciences
Virginia Tech
Narendran Ramakrishnan
Director, Discovery Analytics Center
Thomas L. Phillips Professor of Engineering, Department of Computer Science
Virginia Tech
Gunther Eysenbach
Professor
Senior Scientist, Division of Medical Decision Making and Health Care Research
University of Toronto
Michelle M.H. Şeref
Instructor, Accounting and Information Systems Department, Pamplin College of Business, Virginia Tech
Ph.D. Student, Rhetoric and Writing Program, English Department, Virginia Tech
Samah Gad
Ph.D. Candidate, Department of Computer Science, Virginia Tech
Kathleen T. Kerr
Ph.D. Student, Rhetoric and Writing Program, English Department, Virginia Tech