HOUSE_OVERSIGHT_017037.jpg
1.84 MB
Extraction Summary
4
People
4
Organizations
2
Locations
7
Events
1
Relationships
4
Quotes
Document Information
Type:
Scientific report / academic paper (supplementary material)
File Size:
1.84 MB
Summary
This document appears to be a page from a scientific paper or supplementary report discussing 'culturomic' approaches to tracking historical epidemics and censorship. It details a comparison between human annotators and algorithms in identifying censorship, and then analyzes historical disease outbreaks (Influenza, Cholera, Polio) using cultural interest data (likely Google Books data). The document bears a House Oversight Bates stamp, suggesting it was part of a document production for a congressional investigation, though the text itself is purely academic.
People (4)
| Name | Role | Context |
|---|---|---|
| Franklin Delano Roosevelt | Historical Figure |
Mentioned regarding increased interest in polio following his election in 1932.
|
| Salk | Scientist/Researcher |
Mentioned regarding the development of the polio vaccine in 1952.
|
| Sabin | Scientist/Researcher |
Mentioned regarding the development of the oral polio vaccine in 1962.
|
| Annotator | Researcher (Unnamed) |
Human researcher whose classifications were compared against an algorithm.
|
Organizations (4)
| Name | Type | Context |
|---|---|---|
|
Mentioned regarding user search habits during influenza epidemics.
|
||
| CDC |
Centers for Disease Control; referenced regarding surveillance results.
|
|
| Cambridge World History of Human Diseases |
Source for historical epidemic dates.
|
|
| House Oversight Committee |
Implied via Bates stamp 'HOUSE_OVERSIGHT_017037'.
|
Timeline (7 events)
Locations (2)
| Location | Context |
|---|---|
|
Location of the 1916 polio epidemic.
|
|
|
Region affected by specific cholera epidemics.
|
Relationships (1)
correspondence between the annotator and our algorithm was 81%... and 93%
Key Quotes (4)
"Taken together, the conclusions of a scholarly annotator researching one name at a time closely matched those of our automated approach."Source
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Quote #1
"These findings confirm that our computational method provides an effective strategy for rapidly identifying likely victims of censorship given a large pool of possibilities."Source
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Quote #2
"Disease epidemics have a significant impact on the surrounding culture"Source
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Quote #3
"We therefore reasoned that culturomic approaches might be used to track historical epidemics."Source
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Quote #4
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