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Macroanalysis (Topics in the Digital Humanities)
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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This work sheds a light on the computational examination of the textual data that enable scholars to articulate new questions about the certain literary databases without close-reading them. The questions asked in this book cover the issues like the historical place of individual texts, authors and genres in relation to a larger literary contexts, the literary production in terms of growth and decline over time or within regions or within demographic groups, literary patterns and lexicons over t ...more
Super geeky book but packed with interesting insights. It's a little hard to read, especially the first few chapters as Jockers makes a quite academic introduction on the subject, the field and focuses most of the examples on Irish literature. Nothing against Irish-American literature, but it turns a little too academic for my taste. Once you survive those two chapters, the rest of the book is wonderful and full of ideas and experiments that can be tried. If you're into digital methods of litera ...more
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!
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
May 17, 2017 Vivian Halloran rated it it was amazing · review of another edition
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.
A really introduction to automated textual analysis. Non-technical but conceptually clear, short but offering an overview of numerous approaches (the use of metadata, stylistic analysis, topic modelling and influence between works). Highly recommended!
Molt bona lectura. Dirigit a investigadors que treballen en literatura com a introducció a l'anàlisi quantitativa. Molt útil per a formar el marc teòric d'anàlisi macro en literatura, i dona bones pistes sobre la metodologia.
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 Liz 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
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
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 John 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.