Jodie Archer

Matthew L. Jockers

"When a story captures the imagination of millions, that's magic. Can you qualify magic? Archer and Jockers just may have done so."—Sylvia Day, New York Times bestselling author Ask most people about massive success in the world of fiction, and you'll typically hear that it's a game of hazy crystals balls. The sales figures of E. L. James or Dan Brown seem to be freakish—random occurrences in an unknowable market. So often we hear that nothing but hype explains their success. 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 tell-tale signs of success all over their pages? Thanks to Jodie Archer and Matthew Jockers, 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 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 20,000 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. This book explains groundbreaking text mining research in accessible terms and offers a new perspective on the New York Times bestseller list. It is big-idea book about the relationship between creativity and technology that will be provocative to anyone interested in how analytics have already transformed the worlds of finance, medicine and sports. But at heart it 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

Se perguntarmos para a maioria das pessoas sobre sucesso no mundo dos livros de ficção, vamos ouvir que é um jogo incerto de bolas de cristal. As vendas de E. L. James ou de Dan Brown parecem uma excentricidade — ocorrências aleatórias em um mercado incompreensível. É frequente ouvirmos que só a moda justifica o sucesso que fazem. Mas e se houvesse um algoritmo que pudesse revelar um DNA secreto de best-sellers, independente do gênero?

Tudo o que você precisa saber para escrever um livro campeão de vendas

O segredo do best-seller

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.

Digital Methods and Literary History

Macroanalysis

Přemýšleli jste někdy nad tím, co přivedlo stovky tisíc čtenářů po celém světě ke knižním hitům jako Zmizelá, Dívka ve vlaku nebo k trilogii Milénium? Co kdyby existoval algoritmus, který by uměl předpovědět, ze kterých románů se stanou #1 knižního trhu? Autoři zpracovali data z více než 20 000 románů vydaných za posledních padesát let a přišli s odvážným tvrzením – až s 97% jistotou lze předem určit, jestli rukopis bestsellerový potenciál má!

Šifra mistra bestselleru

Hat „50 Shades of Grey" auch Ihre Kasse kräftig klingeln lassen? Und haben auch Sie sich gefragt: „Warum?" Verlagsprofi Jodie Archer und Englisch-Professor Matthew Jockers haben einen Algorithmus entwickelt, der die Antwort darauf gibt – und der mit 97-prozentiger Genauigkeit vorhersagen kann, welche Schmöker zu Bestsellern werden. Archer und Jockers haben viel Überraschendes über unser Leseverhalten und das Erfolgsrezept fesselnder Romane herausgefunden, zum Beispiel: Menschliche Nähe kommt an, Sex (meistens) nicht. Dieses Buch, welches bereits Furore in der deutschen Presse gemacht hat, ist etwas für alle, die Belletristik lesen, verkaufen, einkaufen, lektorieren ...

Was uns ein bahnbrechender Algorithmus über Bücher, Storys und das Lesen verrät

Der Bestseller-Code

"When a story captures the imagination of millions, that's magic. Can you qualify magic? Archer and Jockers just may have done so."—Sylvia Day, New York Times bestselling author 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? Thanks to Jodie Archer and Matthew Jockers, 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. This book explains groundbreaking text-mining research in accessible terms and offers a new perspective on the New York Times bestseller list. It's a big-idea book about the relationship between creativity and technology that will be provocative to anyone interested in how analytics have already transformed the worlds of finance, medicine, and sports. But at heart it 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.

Anatomy of the Blockbuster Novel

This sneak peek teaser - featuring literary giants John Grisham and Danielle Steele - from Chapter 2 of The Bestseller Code, a groundbreaking book about what a computer algorithm can teach us about blockbuster books, stories, and reading, reveals the importance of topic and theme in bestselling fiction according to percentages assigned by what the authors refer to as the “bestseller-ometer.” Although 55,000 novels are published every year, only about 200 hit the lists, a commercial success rate of less than half a percent. When the computer was asked to “blindly” select the most likely bestsellers out of 5,000 books published over the past thirty years based only on theme, it discovered two possible candidates: The Accident by Danielle Steel and The Associate by John Grisham. The computer recognized quantifiable patterns in their seemingly opposite, but undeniably successful writing careers with legal thrillers and romance. In Chapter 2, Archer and Jockers analyze this data and divulge the most and least likely to best sell topics and themes in fiction with a human discussion of the “why” behind these results. The Bestseller Code is a big-idea book about the relationship between creativity and technology. At heart it is a celebration of books for readers and writers—a compelling investigation into how successful writing works.

Becoming Bestsellers: John Grisham and Danielle Steel (Sample from Chapter 2 of THE BESTSELLER CODE)

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.

Matthew L. Jockers

About

Books

Join the club