The Bestseller Code: Anatomy of the Blockbuster Novel

  • The Bestseller Code Anatomy of the Blockbuster Novel
  • The Bestseller Code Anatomy of the Blockbuster Novel
  • The Bestseller Code Anatomy of the Blockbuster Novel
  • The Bestseller Code Anatomy of the Blockbuster Novel
  • The Bestseller Code Anatomy of the Blockbuster Novel
  • THE BESTSELLER CODE (book review)
  • Can Big Data Predict The Next Bestseller | Simplilearn
  • The Bestseller Code: Anatomy of the Blockbuster Novel
  • The Bestseller Code: Anatomy of the Blockbuster Novel
  • The Bestseller Code: Anatomy of the Blockbuster Novel
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Amazon Price: £9.99 (as of June 26, 2017 4:17 am – Details). Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on the Amazon site at the time of purchase will apply to the purchase of this product.

Also available on amazon.com for £9.99 (as of June 3, 2017 6:57 pm – Details). Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on the Amazon site at the time of purchase will apply to the purchase of this product.

What if an algorithm could predict which manuscripts would become mega-bestsellers?

Girl on the Train. Fifty Shades. The Goldfinch. Why do some books capture the whole world's attention? What secret DNA do they share? In The Bestseller Code, Archer and Jockers boldly claim that blockbuster hits are highly predictable, and they have created the algorithm to prove it. Using cutting-edge text mining techniques, they have developed a model that analyses theme, plot, style and character to explain why some books resonate more than others with readers. Provocative, entertaining, and ground-breaking, The Bestseller Code explores the hidden patterns at work in the biggest hits and, more importantly, the real reasons we love to read.

Product Details

  • Format: Kindle Edition
  • File Size: 2867 KB
  • Print Length: 238 pages
  • Page Numbers Source ISBN: 1250088275
  • Publisher: Penguin (13 Sept. 2016)
  • Sold by:  Amazon Media EU S.à r.l.
  • Language: English
  • ASIN: B01FVDGRB6
  • Text-to-Speech: Enabled
  • X-Ray: Not Enabled
  • Word Wise: Enabled
  • Enhanced Typesetting: Not Enabled

Customer Reviews

Interesting insights, but, as they admit, the authors found what they were looking for

18 people found this helpful.
 on 14 July 2016
By Martin Turner
This is a fascinating but ultimately futile use of multi-variate analysis to search for common characteristics in best sellers. The authors are aware of the limitations of their method, and point them out, but they still do fall into them.

The telltale signs of a book that’s likely to make the (US) bestseller list

6 people found this helpful.
 on 13 September 2016
By Brian Clegg
Despite all the efforts of publishers, it has always seemed impossible to predict whether or not a book would be runaway bestseller. This isn’t too surprising – it’s the kind of thing that is inherently unpredictable because there are simply so many variables involved. Yet a newly published book suggests it is possible to do just that. Are the authors crazed or brilliant? Neither, really. They have put together a mechanism based on computerised text analysis that is good at spotting bestsellers – and yet, oddly, this doesn’t contradict that inherent unpredictability. Why? Because there are two different levels of bestsellerdom involved – and because I think there’s one bit of information missing from the book (apologies to the authors if I’ve missed it).

The Bestseller Code

2 people found this helpful.
 on 11 September 2016
By Damaskcat
I found this book fascinating reading. The authors wrote a computer programme which could read and analyse books and this is the result. They wanted to see if a computer could predict which books would be best sellers and which wouldn’t, A lot of the time it got things right but with some books it was completely wrong – stating that a book was unlikely to be a best seller when it was actually a blockbuster.

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