Skip to main content
Skip to content
Case File
d-33134House OversightOther

Methodology for extracting Wikipedia biographical data for fame analysis

The passage describes a research protocol for building a database of Wikipedia biographies, including word counts and traffic stats. It contains no allegations, financial flows, or connections to powe Outlines steps to collect Wikipedia articles of people born 1800‑1980 via DBpedia. Details extraction of article word counts and March 2010 page‑view statistics. Describes using Wikipedia categories

Date
November 11, 2025
Source
House Oversight
Reference
House Oversight #017028
Pages
1
Persons
0
Integrity
No Hash Available

Summary

The passage describes a research protocol for building a database of Wikipedia biographies, including word counts and traffic stats. It contains no allegations, financial flows, or connections to powe Outlines steps to collect Wikipedia articles of people born 1800‑1980 via DBpedia. Details extraction of article word counts and March 2010 page‑view statistics. Describes using Wikipedia categories

Tags

dbpediaoccupational-classificationwikipediaresearch-methodologydata-collectionhouse-oversight

Ask AI About This Document

0Share
PostReddit

Extracted Text (OCR)

EFTA Disclosure
Text extracted via OCR from the original document. May contain errors from the scanning process.
known, their article will be a member of a “decade_births” category such as “1890s_births” and “1930s_births”. We treat these individuals as if born at the beginning of the decade. For every parsed article, we append metadata relating to the importance of the article within Wikipedia, namely the size in words of the article and the number of page views which it obtains. The article word count is created by directly accessing the article using its URL. The traffic statistics for Wikipedia articles are obtained from http://stats.grok.se/. Figure $10a displays the number of records parsed from Wikipedia and retained for the final cohort analysis. Table S7 displays specific examples from the extraction’s output, including name, year of birth, year of death, approximate word count of main article and traffic statistics for March 2010. 1) Create a database of records referring to people born 1800-1980 in Wikipedia. a. Using the DBPedia framework, find all articles which are members of the categories ‘{700_births’ through ‘1980_births’. Only people both in 1800-1980 are used for the purposes of fame analysis. People born in 1700-1799 are used to identify naming ambiguities as described in section III.7.A.7 of this Supplementary Material. b. For all these articles, create a record identified by the article URL, and append the birth year. c. For every record, use the URL to navigate to the online Wikipedia page. Within the main article body text, remove all HTML markup tags and perform a word count. Append this word count to the record. d. For every record, use the URL to determine the page’s traffic statistics for the month of March 2010. Append the number of views to the record. l1.7.A.2 — Identification of occupation for individuals appearing in Wikipedia. Two types of structural elements within Wikipedia enable us to identify, for certain individuals, their occupation. The first, Wikipedia Categories, was previously described and used to recognize articles about people. Wikipedia Categories also contain information pertaining to occupation. The categories “Physicists”, “Physicists by Nationality’, “Physicists stubs”, along with their subcategories, pinpoint articles of relating to the occupation of physicist. The second are Wikipedia Lists, special pages dedicated to listing Wikipedia articles which fit a precise subject. For physicists, relevant examples are “List of physicists”, “List of plasma physicists” and “List of theoretical physicists”. Given their redundancy, these two structural elements, when used in combination provide a strong means of identifying the occupation of an individual. Next, we selected the top 50 individuals in each category, and annotated each one manually as a function of the individual's main occupation, as determined by reading the associated Wikipedia article. For instance, “Che Guevara’ was listed in Biologists; so even though he was a medical doctor by training, this is not his primary historical contribution. The most famous individuals of each category born between 1800 and 1920 are given in Appendix. In our database of individuals, we append, when available, information about the occupations of people. This enables the comparison, on the basis of fame, of groups of individuals distinguished by their occupational decisions. 2) Associate Wikipedia records of individuals with occupations using relevant Wikipedia “Categories” and “Lists” pages. For every occupation to be investigated : a. Manually create a list of Wikipedia categories and lists associated with this defined occupation. b. Using the DBPedia framework, find all the Wikipedia articles which are members of the chosen Wikipedia categories. 20

Technical Artifacts (4)

View in Artifacts Browser

Email addresses, URLs, phone numbers, and other technical indicators extracted from this document.

Phone1700-1799
Phone1800-1980
URLhttp://stats.grok.se
Wire Refreferring

Forum Discussions

This document was digitized, indexed, and cross-referenced with 1,400+ persons in the Epstein files. 100% free, ad-free, and independent.

Annotations powered by Hypothesis. Select any text on this page to annotate or highlight it.