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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 Update2024-03-28 02:11:39AM
Last Indexed2024-03-28 02:24:37AM

Solr Fields

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accelerated_reader_reading_level
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auth_author2
Jockers, Matthew Lee, 1966-
author
Archer, Jodie
author2-role
Jockers, Matthew Lee,1966-author
author_display
Archer, Jodie
available_at_catalog
Carmichael
Central
North Natomas
Sylvan Oaks
Valley Hi-North Laguna
detailed_location_catalog
Carmichael
Central
North Natomas
Sylvan Oaks
Valley Hi-North Laguna
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"--
format_catalog
Book
format_category_catalog
Books
id
2adf3679-31a7-3696-0f58-7556a11b3c47
isbn
9781250088277
itype_catalog
Adult Book Non-Fiction
last_indexed
2024-03-28T09:24:37.294Z
lexile_score
-1
literary_form
Non Fiction
literary_form_full
Non Fiction
local_callnumber_catalog
028.9 A671 2016
owning_library_catalog
Sacramento Public Library
owning_location_catalog
Carmichael
Central
North Natomas
Sylvan Oaks
Valley Hi-North Laguna
primary_isbn
9781250088277
publishDate
2016
publisher
St. Martin's Press
recordtype
grouped_work
subject_facet
Best sellers -- United States
Books and reading -- United States
Fiction -- Authorship
Popular literature -- United States
Publishers and publishing -- United States
title_display
The bestseller code : anatomy of the blockbuster novel
title_full
The bestseller code : anatomy of the blockbuster novel / Jodie Archer & Matthew L. Jockers
title_short
The bestseller code
title_sub
anatomy of the blockbuster novel
topic_facet
Authorship
Best sellers
Books and reading
Fiction
Popular literature
Publishers and publishing

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