Week 10, 11/1

Text Analysis and Visualizations

Text Analysis: “What is text that we may read it in all
its forms and genres, and find meaning in the statistical behaviour of its
words? What are we that we may find the marks on the pages of books
intelligible and put them there so that others of our kind may read?”

“Reduction of text to data is a trade-off: manipulability, including quantification
and other transformations, is gained; meaning, and with it ‘context’
as a meaningful term, is lost. Effectively all would indeed be lost as far as
the humanities are concerned if the change were one-way, the machine substituted
for human intelligence. Nothing like that is the case for scholarship.
Like other tools, computing augments it, gives it greater reach. Furthermore,
because the computer is, as we will see, dynamically reconfigurable
by design, it can in turn be augmented with new intelligence. Computing
machines and scholarly intelligence change each other, recursively.”

– Willard McCarty, Text and Genre in Reconstruction (pp. 1-2 )

Text Analysis Examples:
a.       http://blogs.ft.com/westminster/2010/06/budget-word-cloud/
b.      2007 State of the Union
c.       Speech Wars
d.      When the writings of Agatha Christie are subjected to Text Analysis, we can learn a lot
e. John Burrows “Never Say Always Again” in Text and Genre in Reconstruction. Effects of Digitalization on Ideas, Behaviours, Products and Institutions (ed. Willard McCarty)
f. TextStat (text analysis and concordance software)
g. Frequency Lists (Mark Davies)

Fri 11/5 Guest: Dr. David S. Heineman, Communication Studies

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