Literature and online resources

A short list of reading material I found useful:

  • Popping R., Computer-Assisted Text Analysis (2000).
  • David Blei, et al., Latent Dirichlet Allocation, in Journal of Machine Learning Research 3 (2003) 993-1022, Link
  • Franco Moretti, Graphs, Maps, Trees (2005). Link to google books
  • Steven B., E. Klein, and E. Loper, Natural Language Processing with Python (2009). (Online book updated to Python 3)
  • David M. Blei, Topic Modeling and Digital Humanities, in Journal of Digital Humanities 2,1 (2012), Link
  • Elijah Meeks and Scott B. Weingart, The Digital Humanities Contribution to Topic Modeling, Journal of Digital Humanities 2,1 (2012), Link
  • Benjamin M. Schmidt, Words Alone: Dismantling Topic Models in the Humanities, in Journal of Digital Humanities 2,1 (2012), Link
  • Seth van Hooland, Ruben Verborgh and Max De Wilde, Cleaning Data with OpenRefine, on The Programming Historian (2013).
  • Mat L. Jockers, Macroanalysis (2013), Link to google books
  • Mat L. Jockers and David Mimno, ‘Significant Themes in 19th-Century Literature‘ (2012).
  • Franco Moretti, Distant Reading (2013).
  • Evans M.S., A Computational Approach to Qualitative Analysis in Large Textual Datasets. PLoS ONE 9(2): e87908. doi:10.1371/journal.pone.0087908 (2014).
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