A Digital Humanities Approach to the History of Science

Eugenics Revisited in Hidden Debates by Means of Semantic Text Mining
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8359)


Comparative historical research on the the intensity, diversity and fluidity of public discourses has been severely hampered by the extraordinary task of manually gathering and processing large sets of opinionated data in news media in different countries. At most 50,000 documents have been systematically studied in a single comparative historical project in the subject area of heredity and eugenics. Digital techniques, like the text mining tools WAHSP and BILAND we have developed in two successive demonstrator projects, are able to perform advanced forms of multi-lingual text-mining in much larger data sets of newspapers. We describe the development and use of WAHSP and BILAND to support historical discourse analysis in large digitized news media corpora. Furthermore, we argue how text mining techniques overcome the problem of traditional historical research that only documents explicitly referring to eugenics issues and debates can be incorporated. Our tools are able to provide information on ideas and notions about heredity, genetics and eugenics that circulate in discourses that are not directly related to eugenics (e.g., sport, education and economics).


Minimum Wage Text Mining Historical Research Statistical Machine Translation Entity Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Descartes Centre for the History and Philosophy of the Sciences and the ArtsUtrecht UniversityThe Netherlands
  2. 2.ISLAUniversity of AmsterdamThe Netherlands

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