Digital Humanities

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Postgraduate course CALM:

Computer-Assisted Language Mediation (UGent)

• More information: Thursday 18 February, 12:50-13:20 pm (faculteit Economie en Bedrijfskunde, Sint-Pietersplein 7, lokaal 0.013)
• http://www.flw.ugent.be/najemaster

Essential links

Structure of the course

Week 1: general introduction + R + use case 1

Week 2: machine learning + use case 2

Week 3-6: Python tutorial

Week 7-8: in-class preparation of one of the two case studies

Week 9: presentation of the results

Specific aims

• Acquiring basic terminology in the field of DH in general, and distributional semantics and/or sentiment analysis in specific.
• Acquiring hands-on experience in a selected set of computational tools.
• Being able to critically reflect on strengths and weaknesses of these tools.
• Being able to conduct a small-scale case study using these tools, and present the results in a paper and presentation.

Main aim in this course

• Learning how to retrieve, analyze and visualize linguistic patterns
• for research purposes in Translation Studies (distributional semantics)
• for end-user purposes in organizations (sentiment analysis)

Course evaluation

As a consequence

Conduct one of the two use cases and present it in a(n):

• [Oral presentation (deadline: week 9]
• Written assignment (deadline: to be determined)

Online collection of DH-definitions: http://whatisdigitalhumanities.com/

An online guide to DH: http://sites.library.northwestern.edu/dh/

Online companion to DH: http://digitalhumanities.org:3030/companion/view?docId=blackwell/9781405103213/9781405103213.xml

Structured collection of Digital Research Tools: http://dirtdirectory.org/

• DH is a very broad, dynamic field: it attracts many scholars from different backgrounds.
• DH is interdisciplinary in nature: it uses computational tools from other scientific fields.
• DH is empirical in nature: it uses observable data as point of departure.

Added value of introducing digital methods to humanities?

• Computers are faster, more reliable and better in some of the tasks that are inextricably linked to doing research in humanities, such as:
• Finding linguistic phenomena (characters, words, constructions) in large collections of texts (= corpora).
• Adding linguistically relevant information in corpora (POS tagging, lemmatization...).
• Counting instances and visualizing patterns in the data
• Nevertheless, humans outperform computers in asking the relevant questions, selecting the appropriate tools and interpreting the visualized output.

A more specific definition

Key references

Berry, D. M; (2012). Understanding Digital Humanities.

Palgrave MacMillan

Burdick, A., J. Drucker, P. Lunenfeld, T. Presner & J. Schnapp (2012). Digital_Humanities. MIT Press.

Jones, S. E. (2013). The Emergence of the Digital Humanities. Routledge.

Digital Humanities is a field of research:

• which extensively uses digital methods like presentation software, database storage, programming languages, text analysis tools, dynamic visualizations...
• ... in order to gather, organize, analyze,

teach and present scholarly research in the humanities (e.g. literature, linguistics, philosophy and history) ...

• ... with the ultimate goal to ask and answer new questions and view old questions differently.

A definition

A Gentle Introduction to

Digital Humanities

What sits at the intersection

of computational methods

and the traditional pursuits

of the humanities.

Overview of the Google corpus compilation project

Let's get a feel for some really cool research in DH

Evolution of grammar

http://whatisdigitalhumanities.com/

Track the regularization of irregular verbs in US and GB:

• Chided vs. chid: chided:eng_gb_2012,chid:eng_gb_2012,chided:eng_us_2012,chid:eng_us_2012
• Burnt vs. burned: burnt:eng_gb_2012,burned:eng_gb_2012,burnt:eng_us_2012,burned:eng_us_2012

Collective memory

Some really interesting digital tools (we won't be presenting)

By Gert De Sutter

• You can easily find out when (and for how long) a given artist, politician, writer became popular.
• Elvis Presley, Jimi Hendrix, Procol Harum, Marvin Gaye
• Lenin, Stalin, Brezhnev, Andropov, Gorbachev, Yeltsin
• You can even do that for 'years', as a quantification of interest in the present and societal forgetting (e.g., 1900, 1950, 1980)

• Culturomics: the quantitative study of human culture as reflected in (diachronic) language use.
• Building on extreme corpora consisting of digitized books (< Google Books project),
• Scanned, OCR'ed, provided with meta data
• 5 M books (~4% of the complete population), amounting to 500 Bn. tokens, in different languages (not Dutch, though :-(, from 1500-2000.

Michel et al. (2011), "Quantitative Analysis

of Culture Using Millions of Digitized Books", Science 331. [DOI: 10.1126/science.1199644]

History of censorship

• You can easily find out which artist, politician, writer was censored during a given period in a given country.
• Compare Picasso and Chagall in the English and German parts of the Google corpus (Picasso:eng_2012, Picasso:ger_2012)

Some really interesting digital tools we will be presenting

• Presentation software: Prezi, LaTeX
• Web crawling: Site Crawler
• Text analysis: Serendip
• Mapping software: Neatline
• Data visualization software: Cytoscape

• And many many more:
• http://dirtdirectory.org/
• http://sites.library.northwestern.edu/dh/tools-resources/

Historical studies

• Historical epidemiology: e.g., influenza (pandemic).
• History of Warfare: e.g., Taliban.
• History of nations: e.g., Belgium.
• History of food: e.g., hamburger, pizza, steak, pasta, sushi.
• History of science: e.g., Darwin, Galileo, Freud, Einstein.

• Advanced text editing: Sublime Text, Notepad++
• Scripting languages: Python
• Machine learning: Weka
• Statistical analysis and data visualization: R

Foci in culturomics

• Cultural change: which concepts are getting into attention at which point in time (e.g., slavery)?
• Application: history of {diseases, science, food, war}, detection of censorship, prominence in collective memory.

• Linguistic change: what is the evolution of the words used for those concepts (e.g. the Great War vs. World War I)?
• Application: evolution of grammar, lexicography

Just do it yourself!

• http://www.culturomics.org
• http://ngrams.googlelabs.com