The bestseller code
Subtitle: anatomy of the blockbuster novel
By: Jodie Archer & Matthew L. Jockers
Contributors: Jockers, Matthew Lee, 1966- author
Edition: First edition.
Published: 2016
Language: eng
Number of pages: 242
ISBN-13: 9781250088277
Subjects: Books and reading; Best sellers; Popular literature; Authorship; Publishers and publishing; Fiction
Description: "What if there was an algorithm that could predict which novels become mega-bestsellers? Are books like Dan Brown's The Da Vinci Code and Gillian Flynn's Gone Girl the Gladwellian outliers of publishing? The Bestseller Code boldly claims that the New York Times bestsellers in fiction are predictable and that it's possible to know with 97% certainty if a manuscript is likely to hit number one on the list as opposed to numbers two through fifteen. The algorithm does exist; the code has been cracked; the results are in; and they are stunning. The system analyzes themes, plot, character, pacing, even the frequency of words and punctuation, to predict which stories will resonate with readers. A 28-year-old heroine is a big plus. So is realism. Giving 30% of your novel to only two specific topics. And if you can include a dog rather than a cat and few sex scenes, you have a better chance of writing a bestselling novel. The project is an investigation into our intellectual and emotional responses as humans and readers to books of all genres. It is a big idea book that will appeal to fans of The Black Swan by Nassim Taleb, a book for data-mining nerds, as well as a book about writing, reading, and publishing. Anyone who has ever wondered why Gone Girl, Girl on the Train or The Girl With the Dragon Tattoo captured so many readers worldwide will find their interest piqued"--
Notes: Includes bibliographical references.
Table of contents: title: The bestseller-ometer, or, How text mining might change publishing; title: The godparents, or, Why you must take time to date; title: The lists: theme; title: The sensations, or, How to form some perfect curves; title: The lists: plot; title: The debutantes, or, Why every comma matters; title: The lists: style; title: The noirs, or, What the girl needs; title: The lists: character; title: The one, or, When the algorithm winked; title: The lists: all data points; title: Epilogue: The machine-written novel, or, Why authors really matter; title: Postscript, or, Some background on method.