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Macroanalysis (Topics in the Digital Humanities)
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Macroanalysis (Topics in the Digital Humanities)

4.03  ·  Rating details ·  79 ratings  ·  11 reviews
In this volume, Matthew L. Jockers introduces readers to large-scale literary computing and the revolutionary potential of macroanalysis--a new approach to the study of the literary record designed for probing the digital-textual world as it exists today, in digital form and in large quantities. Using computational analysis to retrieve key words, phrases, and linguistic pa ...more
Kindle Edition, 208 pages
Published March 15th 2013 by University of Illinois Press
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4.03  · 
Rating details
 ·  79 ratings  ·  11 reviews

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Katherine McCauley
If you're at all interested in this topic, this book is a good way to go. It's casual but also knowledgeable, and it's also pleasingly short. More short books! Thank you for listening.
Nov 04, 2015 rated it it was amazing  ·  review of another edition
Shelves: dissertation
Recommended reading for anyone interested in digital text analysis and literary history. Jockers' writing is clear and accessible, even for those who may have never programmed. He makes compelling arguments for the necessity of moving beyond close reading and provides concise, apt examples of the potential - and shortcomings - of digital text analysis. I haven't enjoyed reading academic work like this in a long time!
Elvin Meng
A good, gentle introduction to the field. Delivery is very clear and accessible, but there are some downsides to this clarity. Statistical details (the very thing that makes data-based arguments stronger than gross generalizations) are sacrificed for the elegance of deliverance, and the examples for statistical techniques can come across as a bit puerile and (dangerously) oversimplified for anyone with any kind of statistics background. The author also makes little attempt to *show* how this for ...more
Vivian Halloran
This was a thoroughly enjoyable read. The prose is lucid, there are ample definitions of key terms, and the overall tone is personable and disarming. The discussion of his work on Irish and Irish American novels was engaging--his anecdotes about the various trials and errors involved in this research made me realize the value of macro analysis as a complement to close reading.
Accessible and firm argument for macroanalysis in the humanities, but I found it a bit lighter on methodological claims than what I would've personally preferred for a monograph unified by method rather than period/theme.
Jan 25, 2013 rated it really liked it  ·  review of another edition
This book is terrific, immagine a crazy litterate that create a statistical model to verify who were the most important authors in the english language litterature (Austen and Scott) and the most important argument about which authors wrote. Then you can immagine more or less this book, that is not easy at all, but so interesting! Using Latent Dirichlet Allocation the author shows this topoi and the other related to them as if they were a cloud but it's better if you co on his page and try this ...more
Jul 15, 2013 rated it really liked it  ·  review of another edition
And now I remember why I wanted to learn R over summer break. This book assumes at least a passing familiarity with Digital Humanities (at least, it assumes that you've heard of it) and is mostly a well-curated and intriguing tour of what the Stanford Literary Lab has been up to over the past five years. Jockers' work is especially useful because he has a very clear idea of why he is doing what he is doing (which does not always come through in the shorter discussions of his work). His focus isn ...more
Jun 17, 2016 rated it really liked it  ·  review of another edition
A refreshingly approachable introduction to the complex world of big data analysis in the humanities. Given that a good chunk of his audience could find programming jargon intimidating, Matthew Jockers does a great job explaining his work and the theory behind it without overwhelming readers. While I would have enjoyed an appendix with more information to help apply his methods, he has also offered Text Analysis with R for Students of Literature for those interested in learning more about the te ...more
Stephen Houser
Good introduction to digital humanities and text-mining. Thought provoking in how he "fingerprinted" texts with 40+ style features and 500+ theme features. Not enough detail in the book to reproduce the work, but enough to get a start in the field. Footnotes, footnotes, footnotes...
Jul 15, 2014 rated it really liked it
A surprisingly clear book on using data mining techniques to discover patterns in Victorian Literature. Not sure I can readily accept all the conclusions in the book, but the techniques used are inspiring.
James Igoe
May 31, 2014 rated it really liked it
Great foray into data mining literature, although at times a bit tedious and redundant. Conceptually useful, for general concepts in data mining, but with no actual coding.
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