Macroanalysis: Digital Methods and Literary History (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 patterns across thousands of texts in digital libraries, researchers can draw conclusions based on quantifiable evidence regarding how literary trends are employed over time, across periods, within regions, or within demographic groups, as well as how cultural, historical, and societal linkages may bind individual authors, texts, and genres into an aggregate literary culture. Moving beyond the limitations of literary interpretation based on the "close-reading" of individual works, Jockers describes how this new method of studying large collections of digital material can help us to better understand and contextualize the individual works within those collections.

Computers & Technology

Jockers, Matthew L.

Software

University of Illinois Press

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 patterns across thousands of texts in digital libraries, researchers can draw conclusions based on quantifiable evidence regarding how literary trends are employed over time, across periods, within regions, or within demographic groups, as well as how cultural, historical, and societal linkages may bind individual authors, texts, and genres into an aggregate literary culture. Moving beyond the limitations of literary interpretation based on the "close-reading" of individual works, Jockers describes how this new method of studying large collections of digital material can help us to better understand and contextualize the individual works within those collections.

“Non-formulaic, eye-opening, deeply-researched ― and really worth your time.”― GQ 
Jodie Archer and Matthew L. Jockers' The Bestseller Code: Anatomy of the Blockbuster Novel is a big idea book that explains their text-mining research through a groundbreaking look at the New York Times bestseller list. It explores the relationship between creativity and analytics, picking bestsellers via algorithm with a high degree of accuracy. We know that technology has transformed the worlds of finance, medicine, and sports; now it's making its mark on books.
Ask most people about massive success in the world of fiction, and you’ll typically hear that it’s a game of hazy crystal balls. The sales figures of E. L. James or Dan Brown seem to be freakish―random occurrences in an unknowable market. But what if there were an algorithm that could reveal a secret DNA of bestsellers, regardless of their genre? What if it knew, just from analyzing the words alone, not just why genre writers like John Grisham and Danielle Steel belong on the lists, but also that authors such as Junot Diaz, Jodi Picoult, and Donna Tartt had telltale signs of success all over their pages? 
The algorithm exists; the code has been cracked; and the results bring fresh new insights into how fiction works and why we read. The Bestseller Code offers a new theory for why Fifty Shades of Grey sold so well. It sheds light on the current craze for dark heroines. It reveals which themes tend to sell best. And all with fascinating supporting data taken from a five-year study of twenty thousand novels. Then there is the hunt for "the one"―the paradigmatic example of bestselling writing according to a computer's analysis of thousands of points of data. The result is surprising, a bit ironic, and delightfully unorthodox.
At heart, The Bestseller Code is a celebration of books for readers and writers―a compelling investigation into how successful writing works, and a fresh take on our intellectual and emotional response to stories.

The Bestseller Code: Anatomy of the Blockbuster Novel

Business & Money

Archer, Jodie

Industries

St.Martin's Press

Now in its second edition, Text Analysis with R provides a practical introduction to computational text analysis using the open source programming language R. R is an extremely popular programming language, used throughout the sciences; due to its accessibility, R is now used increasingly in other research areas. In this volume, readers immediately begin working with text, and each chapter examines a new technique or process, allowing readers to obtain a broad exposure to core R procedures and a fundamental understanding of the possibilities of computational text analysis at both the micro and the macro scale. Each chapter builds on its predecessor as readers move from small scale “microanalysis” of single texts to large scale “macroanalysis” of text corpora, and each concludes with a set of practice exercises that reinforce and expand upon the chapter lessons. The book’s focus is on making the technical palatable and making the technical useful and immediately gratifying. 
Text Analysis with R is written with students and scholars of literature in mind but will be applicable to other humanists and social scientists wishing to extend their methodological toolkit to include quantitative and computational approaches to the study of text. Computation provides access to information in text that readers simply cannot gather using traditional qualitative methods of close reading and human synthesis. This new edition features two new chapters: one that introduces dplyr and tidyr in the context of parsing and analyzing dramatic texts to extract speaker and receiver data, and one on sentiment analysis using the syuzhet package. It is also filled with updated material in every chapter to integrate new developments in the field, current practices in R style, and the use of more efficient algorithms.

Text Analysis with R: For Students of Literature (Quantitative Methods in the Humanities and Social Sciences)

Thalken, Rosamond

Springer

Text Analysis with R for Students of Literature is written with students and scholars of literature in mind but will be applicable to other humanists and social scientists wishing to extend their methodological tool kit to include quantitative and computational approaches to the study of text. Computation provides access to information in text that we simply cannot gather using traditional qualitative methods of close reading and human synthesis. Text Analysis with R for Students of Literature provides a practical introduction to computational text analysis using the open source programming language R. R is extremely popular throughout the sciences and because of its accessibility, R is now used increasingly in other research areas. Readers begin working with text right away and each chapter works through a new technique or process such that readers gain a broad exposure to core R procedures and a basic understanding of the possibilities of computational text analysis at both the micro and macro scale. Each chapter builds on the previous as readers move from small scale “microanalysis” of single texts to large scale “macroanalysis” of text corpora, and each chapter concludes with a set of practice exercises that reinforce and expand upon the chapter lessons. The book’s focus is on making the technical palatable and making the technical useful and immediately gratifying.

Text Analysis with R for Students of Literature (Quantitative Methods in the Humanities and Social Sciences)

This practical introduction explores core R procedures and processes and offers a thorough understanding of the possibilities of computational text analysis at both micro and macro scales. Each chapter concludes with a set of practice exercises.

See the best price to sell, buy, or rent books by Jockers, Matthew L.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Jockers, Matthew L.

See the best price to sell, buy, or rent books by Jockers, Matthew L.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Macroanalysis: Digital Methods and Literary History (Topics in the Digital Humanities)

Macroanalysis: Digital Methods and Literary History (Topics in the Digital Humanities)

The Bestseller Code: Anatomy of the Blockbuster Novel

Text Analysis with R: For Students of Literature (Quantitative Methods in the Humanities and Social Sciences)

Text Analysis with R for Students of Literature (Quantitative Methods in the Humanities and Social Sciences)

Text Analysis with R for Students of Literature (Quantitative Methods in the Humanities and Social Sciences)