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Digital Humanities: A brief introduction to the field


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Lecture given at ADEPT Summer School, Queen Mary University of London, 23 July 2015

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Digital Humanities: A brief introduction to the field

  1. 1. Digital Humanities A brief introduction to the field Dr Anouk Lang Department of English University of Edinburgh @a_e_lang Thurs 23 July 2015 6-7.30pm Queen Mary University of London #adpsummer
  2. 2. “To infinity & beyond”: Where we’re headed Working with data: where are the pitfalls? - structured vs. unstructured Overview of the field - historical background and debates Sample projects and tools - textual, spatial and network analysis Resources - summer schools, workshops, teach-yourself tutorials, Twitter @a_e_lang | | #adpsummer
  3. 3. Working with data as a humanities scholar Ben Schmidt, “Gendered language in teacher reviews”  interdisciplinary  serious fun @a_e_lang | | #adpsummer Randall Munroe, “Correlation”, XKCD,
  4. 4. @a_e_lang | | #adpsummer
  5. 5. What are the limitations?  data collection  sampling What is obscured?  gender of reviewers  context  gender of reviewees  field size @a_e_lang | | #adpsummer
  6. 6. Data: you’re not just using it but producing it  Facebook’s “emotional contagion” study  Facebook voting study  Homicide Watch  And, obviously, NSA/GCHQ/etc @a_e_lang | | #adpsummer
  7. 7. Data: structured vs. unstructured  information that is organised in some way  vs information that comes without a data model @a_e_lang | | #adpsummer
  8. 8. @a_e_lang | | #adpsummer Rate My Professors: one data model
  9. 9. Data: structured vs. unstructured  information that is organised in some way  vs information that comes without a data model  Schmidt’s dataset: partially structured but also in need of some curation  Data from an API, eg. Twitter data @a_e_lang | | #adpsummer
  10. 10. @a_e_lang | | #adpsummer Twitter data: highly structured
  11. 11. @a_e_lang | | #adpsummer Humanities data: often unstructured Image from Flickr: Jason Weinberger, “Mahler Symphony 5, IV Adagietto [page 15]”, CC BY 2.0 licence.
  12. 12. @a_e_lang | | #adpsummer Jad Abumrad and Robert Crulwich, “Vanishing Words”, RadioLab,
  13. 13. Concordancing software: AntConc (Laurence Anthony) Query 1: all instances of look as a simple text string
  14. 14. @a_e_lang | | #adpsummer Text marked up with tags denoting parts of speech
  15. 15. @a_e_lang | | #adpsummer Query 2: all instances of look as a noun (look_NN*)
  16. 16. @a_e_lang | | #adpsummer Query 3: all instances of look as a verb (look_VV*) followed by a preposition (*_II) then sorted 1R, 2R
  17. 17. @a_e_lang | | #adpsummer Query 4: all instances of the lemma look* sorted 1R, 2R
  18. 18. @a_e_lang | | #adpsummer Pos-tagging errors: look_NN* != look as a noun
  19. 19. Data: always contingent, never objective  Johanna Drucker & the concept of ‘capta’  what kind of data curation is necessary?  who else has come up with categories/data models?  think about how to capture & structure your data early @a_e_lang | | #adpsummer
  20. 20. Overview of the field: Definitional skirmishes Digital Humanities is a field of study in which scholarly applications of technology are used to perform analyses and generate insights that would be difficult or impossible to achieve without the help of technology. “digital humanities is more akin to a common methodological outlook than an investment in any one specific set of texts or even technologies”. (Matthew Kirschenbaum) @a_e_lang | | #adpsummer
  21. 21. @a_e_lang | | #adpsummer Or you could crowdsource the definition …
  22. 22. @a_e_lang | | #adpsummer Or you could crowdsource the definition …
  23. 23. @a_e_lang | | #adpsummer Historical antecedents: Humanities Computing Roberto Busa, IBM & the Index Thomisticus Livia Canestraro, one of the female punchcard operators for the Index Thomisticus. CC-BY-NC, license by permission of CIRCSE Research Centre, Università Cattolica del Sacro Cuore, Milan. Via Melissa Terras, /2013_10_01_archive.html
  24. 24. @a_e_lang | | #adpsummer Disciplinary antecedents • corpus linguistics, computational linguistics & NLP • GIS (Geographic Information System / Science) • within History, Cliometrics • others …
  25. 25. @a_e_lang | | #adpsummer Readings giving historical background • Kirschenbaum, Matthew G. ‘What Is Digital Humanities and What’s It Doing in English Departments?’ ADE Bulletin 150 (2010): 1–7. /2011/01/kirschenbaum_ade150.pdf. • Liu, Alan. ‘The Meaning of the Digital Humanities’. PMLA 128.2 (2013): 409–423. • Hockey, Susan. ‘The History of Humanities Computing’. In Susan Schreibman, Ray Siemens and John Unsworth, eds., A Companion to Digital Humanities (Oxford: Blackwell, 2004).
  26. 26. @a_e_lang | | #adpsummer Some broad debates and tensions in the field • from outside the field: too empiricist, too positivistic, too uncritical of the use of computers • from within the field: not sufficiently statistically/algorithmically literate, use of black boxes • too apolitical: where are race, gender, & identity? • too focused on literature • “you’re not a real digital humanist unless you can code” • “more hack, less yack”
  27. 27. Examples of projects and tools @a_e_lang | | #adpsummer Image from In the Forbidden Land: An account of a journey in Tibet ... With a map and two hundred and fifty illustrations (1898), p.154. From the British Library’s Flickr collection of images in the public domain Textual analysis Mapping Network analysis
  28. 28. 0 day lydia dear replied felt cried aunt hear uncle charlotte 1 wickham made till evening added world knew married father visit 2 lady man young catherine brother ladies happiness half friends settled 3 make great give hope thought pleasure present general affection conversation 4 time sister mother love feelings ill speak leave meryton life 5 mr darcy bingley miss collins mind london civility convinced feeling 6 mrs bennet family long gardiner morning town found character coming 7 elizabeth jane letter longbourn happy answer kind left kitty reason 8 good friend house lizzy subject sisters father netherfield told home 9 room manner daughter heard sir moment looked woman immediately began For more on topic modelling, start at Vol. 2 issue 1, Journal of Digital Humanities: @a_e_lang | | #adpsummer Textual analysis: Topic modelling
  29. 29. @a_e_lang | | #adpsummer Textual analysis: Stylometry Authorship attribution: “the science of inferring characteristics of the author from the characteristics of documents written by that author” (Juola 2006). Deciphering The Dynamiter
  30. 30. @a_e_lang | | #adpsummer Textual analysis: Stylometry Deciphering The Dynamiter green = Fanny black = Fanny black = Robert orange = Robert red = authorship uncertain
  31. 31. @a_e_lang | | #adpsummer Textual analysis: Stylometry Clear differentiation vs. overlap between authors
  32. 32. @a_e_lang | | #adpsummer Using DH in research-led teaching
  33. 33. @a_e_lang | | #adpsummer Spatial analysis: digital maps Salem Witch Trials (U Virginia) Mapping Modernist Paris (Lang) LitLong (Edinburgh U) Mapping the Lakes (Ian Gregory)
  34. 34. @a_e_lang | | #adpsummer Spatial analysis: digital maps
  35. 35. Franco Moretti, “Network Theory, Plot Analysis”, New Left Review 68 (2011): 81. Also available as a LitLab pamphlet: see @a_e_lang | | #adpsummer Network analysis and visualisations
  36. 36. Moretti, “Network Theory”, 87. @a_e_lang | | #adpsummer
  37. 37. @a_e_lang | | #adpsummer Moretti, “Network Theory”, 87.
  38. 38. Further resources • DHOxSS: DH Summer School at Oxford • Lancaster Summer Schools • Further afield: DHSI, HILT, DH@Leipzig • The Programming Historian ( • MOOCs, eg. IVMOOC, Coursera, FutureLearn • Training courses at your institution, eg. ArcGIS • Teach-yourself tutorials, eg. Codecademy • DH Q&A @a_e_lang | | #adpsummer
  39. 39. Matthew Jockers, “Revealing Sentiment and Plot Arcs with the Syuzhet Package”, blog post, Matthew L. Jockers 2 Feb. 2015. www.matthewjockers. net/2015/02/02/syuzhet/. Code at @a_e_lang | | #adpsummer
  40. 40. Eileen Clancy, “A Fabula of Syuzhet II: Continuing the tale of digital humanities and sentiment analysis”. Storify of tweets from 24 Mar-10 April 2015. wyork/a-fabula-of-syuzhet-ii. @a_e_lang | | #adpsummer
  41. 41. until Syuzhet provides filters that don’t cause ringing artifacts [extra lobes introduced into a graph by an ideal low-pass filter], it is likely that most foundation shapes will be inaccurate representations of the stories’ true plot trajectories. Since the foundation shape may in places be the opposite of the emotional trajectory, two foundation shapes may look identical despite having opposing emotional valences. Jockers’s claim … may be due more to ringing artifacts than to an actual similarity between the emotional structures of the analyzed novels. Annie Swafford, “Problems with the Syuzhet Package”, blog post, Anglophile in Academia, 2 March 2015.
  42. 42. adapted from Allie Brosh, Hyperbole and a Half ( @a_e_lang | | #adpsummer