Can We Actually Use Data to Predict Bestsellers?

data, code, algorithm, publishers, bestsellers, new york times, booksThe upcoming book The Bestseller Code is getting a great deal of buzz, forcing many of us to ask the question, Can one genuinely predict what kind of book will become a New York Times bestseller (typically considered the most prestigious bestseller list)?

The promise of a formula for predicting a bestseller is getting many in the publishing industry and those who write about books excited, or at least curious. Several journalists contacted me for an opinion about the book because of my background in pub-tech and reader analytics. Thus, I became interested in reading it, and St. Martin’s Press was kind enough to provide me with an advance reader copy.

First of all, this is a delightful book to read. I would recommend it as both an entertaining and educational read for anybody interested in the business of books. This is not a magisterial work, like Merchants of Culture by John Thompson, but a book written for the mass market with plenty of anecdotes and examples that readers and authors can relate to.

The “code” is based on some of the latest advances in machine learning as applied to literature, but the authors attempt to simplify the computer science behind the book. There is no mention of “big data” or artificial intelligence—just plain and simple descriptions of what the “black box” does, with references for interested readers to find out more about its inner workings.

Much more.


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Bloomsbury USA Restructures (PW)
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