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The bestseller code: anatomy of the blockbuster novel

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Publisher:
St. Martin's Press,
Pub. Date:
2016.
Language:
English
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"--
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ISBN:
9781250088277
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Grouping Information

Grouped Work ID2adf3679-31a7-3696-0f58-7556a11b3c47
Grouping Titlebestseller code anatomy of the blockbuster novel
Grouping Authorjodie archer
Grouping Categorybook
Grouping LanguageEnglish (eng)
Last Grouping Update2020-09-29 02:32:36AM
Last Indexed2020-09-28 03:09:29AM
Novelist Primary ISBNnone

Solr Details

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auth_author2Jockers, Matthew Lee, 1966-
authorArcher, Jodie.
author2-roleJockers, Matthew Lee,1966-author.
author_displayArcher, Jodie
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display_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"--
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subject_facetBest sellers -- United States
Books and reading -- United States
Fiction -- Authorship
Popular literature -- United States
Publishers and publishing -- United States
title_displayThe bestseller code : anatomy of the blockbuster novel
title_fullThe bestseller code : anatomy of the blockbuster novel / Jodie Archer & Matthew L. Jockers
title_shortThe bestseller code
title_subanatomy of the blockbuster novel
topic_facetAuthorship
Best sellers
Books and reading
Fiction
Popular literature
Publishers and publishing