Transcript here - University of Nottingham

“Doing” Digital
Humanities
A Practical Introduction
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Overview of this talk
• Several strands of DH work
– Barriers to entry, and support available
• DH as a postgrad
• Projects, funding, collaboration: academic DH at
the post-doc level
• Employability
• Resources available
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Textual Analysis
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Corpus tools
Ngrams
Text mining
Topic Modelling
Stylistic Analysis
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Corpus Tools
• Voyant: http://voyant-tools.org/ also
http://hermeneuti.ca/voyeur/tools
• Google Ngram viewer:
http://books.google.com/ngrams
• British National Corpus:
http://www.natcorp.ox.ac.uk/
• BYU Corpora: http://corpus.byu.edu/
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Text Mining, Topic Modelling, Stylistic
Analysis
• All require pre-existing text corpora, more or less
“clean”
• Text Mining
– Statistics, scripting
• Topic Modelling
– Easy to do (sort of); need statistics to analyze
results
• Stylistic Analysis
– Language (R) is unintuitive and statistics-based
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TEXT MINING IS NOT A MAGIC BOX
• Interrogate the box!
• Support can be found:
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DH Seminars
CRAL (for talk about corpora, corpus tools)
Books to learn scripting
DHAnswers (and the internet more generally)
Speak to me
• Some existing interfaces:
http://encyclopedie.uchicago.edu/node/176
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Social Media Research
• Twitter – but also Facebook, YouTube, Flickr, etc
• Twitter’s business model: charge for access to
the “firehose”
• Some free tools
– Webometric Analyst**, Snapbird, the Archivist,
TAGS v3
• Sites and tools constantly changing – keep local
copies of data
• Ethics!
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Databases and Digital Archives
• Creating your own research data archive can be
reasonably straightforward
• MS Access, MySQL Community Edition, others
• Can be moderately easy to use, but less easy to
use well
• Database design classes available on Short
Courses
• Back it up!
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Visualization
• Requires data to visualize
• http://selection.datavisualization.ch/
– Some web scripting libraries
– Some stand-alone tools
• A different way of presenting results; can tie in
with network analysis, geospatial work, etc
• Interpreting the visualizations rigorously often
means understanding underlying data model
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Image Analysis
• Need good-quality images to start with; often
done as part of a larger project
• Processing involves MatLab, maths
• Procedures and algorithms to manipulate signal
data
• Can be used in restoration & conservation,
reading damaged material, archaeology
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Geospatial Work
• Need data from somewhere (can be text data)
• Plotting data on maps can reveal new insights:
http://sappingattention.blogspot.co.uk/2012/11/re
ading-digital-sources-case-study-in.html#more
• Have ArcGIS licenses in DHC!
• Interactive maps likely to require more computing
skills, web hosting, and other barriers (eg:
Neatline is great, and does georectifying, if you
are running Omeka…)
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Network Analysis
• Models relationships between entities (of various
types) as a network
• Social networks are one key type of network, but
have to avoid being reductive
• Requires vector maths to create and interpret
networks
• Good free tools
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Less DIY
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Text encoding, corpus creation
Digitisation, image capture
Interactive geospatial work
Large crowdsourcing projects
Project management
Tool development and infrastructure building
Linked open data
These things tend to require frameworks.
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DH as a postgraduate
• The final goal: thesis
• Something you can build and deploy within three
years, while writing a book
• Institutional support available, but not large
project teams
• Start early; manage your research data well
• (Note: Digital Economy Young Entrepreneur
Scheme)
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Academic Digital Humanities at the Postdoctoral level
• Projects – particularly in academia, much DH
work is “project-based”
• Funding – funded projects of varying lengths
• Collaboration – working in partnership with other
academics and technologists
• Possibility to work in digital humanities in
universities, museums, libraries, not as a lecturer
• Global digital humanities (Europe, US, Canada,
Mexico… Australia, South and Central America)
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Employability
• Experience working with new technologies,
managing projects, learning new skills
• Ability to work collaboratively is a big benefit
• Skills are relevant to employers outside
academia; can be a hiring boost for postdocs
(though this may not last)
• Academic and graduate job markets both
EXTREMELY COMPETITIVE
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Find out more…
• Digitalhumanitiesnow.org
• Books (open access versions online):
– Debates in the Digital Humanities
– Companion to Digital Humanities
• Digital Humanities Quarterly (open access)
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The Joy of Digital Humanities
“The work we do is graphical and structural and
interactive. It’s increasingly material and mobile, and it’s
almost never made alone. Whatever it is, like any
humanities theorizing it opens some doors and shuts
others, but it’s a style of scholarly communication that
differs sharply from the dominant, extravagantly vocal
and individualist verbal expressions of the last fifty to
sixty years. And like any craft it’ll always be underarticulated.”
- Bethany Nowviskie, “Resistance in the Materials”
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Resources Available
• DHC!
• CAS Digital Humanities Seminars
• Me ([email protected],
@EE_Snyder)
• Subject librarians
• Internet: Blogs, DHAnswers, HASTAC, Twitter
• The wider university community
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