prof.dr . toine pieters & dr. pim huijnen utrecht university [email protected]
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Developing a web-application for comparative historical data-mining in public media from different countries. Prof.Dr . Toine Pieters & Dr. Pim Huijnen Utrecht University [email protected] Sheffield, 06/09/2012. Research project: BILAND. - PowerPoint PPT PresentationTRANSCRIPT
DEVELOPING A WEB-APPLICATION FOR
COMPARATIVE HISTORICAL DATA-MINING IN PUBLIC MEDIA
FROM DIFFERENT COUNTRIES
Prof.Dr. Toine Pieters & Dr. Pim Huijnen
Utrecht [email protected]
Sheffield, 06/09/2012
Research project: BILAND
History of mentalities: making explicit tacit beliefs, standards, morals
Casus: Concepts of genetics/eugenics in culture
Development of a digital data-mining tool
Eugenics
Francis Galton(1822-1911)
To improve the genetic quality of the human race Control over sexual reproductionEncouragement of procreation, measures of sterilization and segregation
Research questions (1)
Public discourse not monopolized by “hard-line” eugenics:What did this mean for the dissemination of genetic and eugenic thinking in Dutch public discourse? What were the political and racial connotations of the arguments that circulated in newspapers and how did they become manifest in different domains?
Research questions (2)
Comparison German and Dutch public discourse in the interwar period:How, when and to what extent did discourses about heredity, genetics and eugenics in Germany began to differentiate from the Netherlands?
Research on public debates (1)
Condit (1999):Analysis explicit stances on eugenics
backbone study: 653 articles from American periodicals 1900-1995
Sources:Royal Library The Hague Staatsbibliothek zu Berlin
Research on public debates (2)
Research on public debates (2)
No limitation source materialNo selection issuesNo representativeness issues
Enabling research on hidden debates, mentalities, implicit notions
Keywords (examples)
AncestryLineageDescentStockReproductionRegulationSelection
pure/purityProgressionEvolvementDeteriorationDepravationIsolationsegregation
Research on public debates (2)
No limitation source materialNo selection issuesNo representativeness issues
Enabling research on hidden debates, mentalities, implicit notionsReproducibility of research, from various perspectives
Reproducibility
How does it work? (1)
keywordsQueriesQuantitative analysis
Quantitative analysis
No. of hitsSourcesWord cloud – sentiments, NERTimeline
Named Entity Recognition
GeographicalProper namesInstitutional names
Timeline
Query: Sports + Heredity
How does it work? (2)
LexicaQueriesQuantitative analysisQualitative analysisInsight…and again!
www.biland.nl