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Digital Humanities Lab

DH Tips & Tutorials

Digital Humanities Societies:

Digital Humanities Journals:

Digital Humanities and diversity:

Tools for Text Mining and Topic Modelling:

  • Information on Digital Humanities tools and methods peer reviewed and suited for starters: The Programming Historian. 82 tutorials in English, 45 tutorials are also available in Spanish and 10 tutorials are translated in French. Text analysis tutorials are referred to as ‘distant reading’ (term coined by Franco Moretti);
  • Brilliant fundgrube for a lot of very interesting stuff: Quanthum (they also mention the Programming Historian);
  • Voyant tools;
  • AntConc Tool for concordancing;
  • Lancsbox: Very useful tool that incorporates a lot of methods and knowledge on computational linguistics. Lancsbox will allow you to compare corpora and also cover POS tagging, so you will be able for instance to count verbs, nouns etc. in your corpus;
  • Iramuteq: French G(raphical) U(ser) I(nterface) for text mining in R;
  • Article with a survey of (some) text analysis packages for R. Published in Language Resources and Evaluation, Vol. 53, Issue 4 (December 2019);
  • Further references on tools and tutorials, also on Quanthum, here and here.


  •  Shawn Gram, Ian Milligan and Scott B. Weingart, Exploring big historical data: the historian’s macroscope. Pre-draft version available here.
  •  Ashish Kumar, Avinash Paul, Mastering text mining with R, Packt Publishing.


Text mining in R: