The Bestseller Code: Anatomy of the Blockbuster Novel
Date: September 20, 2016
Сategory: Psychology, Self-Help
ISBN: 1250088275
Language: English
Number of pages: 256 pages
Format: EPUB
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“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.
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.
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