This book will not provide the literary alchemy required to transmute your leaden manuscript into a golden book. It does contain some common sense observations which are not derived from the authors’ model, but a rational person must be skeptical of the notion that text mining and analysis of “word clouds” can be predictive of a book’s commercial success.. There are a lot of problems with the authors’ analytics, and even more with their presentation. Where to start?
- There's no surprise “the Code” (also called “the Model” or the “Bestseller-ometer”) works so well. Success was built in since historic bestsellers are already known, so when they are programmed into the model it “predicts” they’ll sell well. What The Code can’t do is predict the success of an unpublished novel.
- Science is peer-reviewable and this bestseller-ometer hasn’t been peer reviewed. To do that a double-blind test would have to be made by independent investigators to determine if the model produced the claimed results. It would not.
- The authors claim to have analyzed 5 thousand novels published in the last 30 years. First of all, they probably didn’t. Second, predicting future results from past performance is fraught (see Enron and Lucent stock prices). Modern literary tastes differ significantly from those of the past and you are not planning to sell your novel into a 1980s readership or to a Borders store.
- In your heart, Dear Reader, do you honestly believe that when 5 thousand novels were “DNA deconstructed” by the bestseller-ometer, that it could produce the lists on pages 70-71? There is only one way that could have happened and that is for the model to pick up key words like “Jodi Picault,” “David Baldacci,” “Nora Roberts,” “Stephen King,” and “Paulo Coelho” as part of its analytic filtering. Again, hindsight is difficult to overrate.
- Consider these supposedly surprising conclusions revealed by the model. A bestseller must have a dominant theme comprising roughly a third of its word count. And that topic must appeal to millions of readers. And it must have “human closeness.” And, my favorite revelation, conflict drives novels. Who knew?
- If you aren’t put off by the book’s inane claims by page 88, consider the graph of the “measured beats” (a key modeling predictor) in Fifty Shades. You may or may not notice that the vertical axis on the chart is not labeled. That is because “measured beat” is a vague concept, not a scientifically measureable variable. In fact the wavy line on the chart is just a freehand depiction of something, maybe tension, which, by the way, the model can discern infallibly.
- Knowing what you now know about this freehand line derived from Fifty Shades how amazed are you by the authors’ claim that it precisely overlays the freehand line representing the rising and falling of tension in DaVinci Code? Are you awestruck that those two wavy lines are the only two which are exactly alike among the 5 thousand books over 30 years whose DNA were deconstructed by the model? Recall what they say about something too good to be true.
- Do you sincerely believe that a word cloud identification model can determine whether the book has a killer hook in the first 40 pages? What would a hook look like in a word cloud?
This book is junk science and it relies on a scientifically illiterate readership (and St. Martin’s Press’s promotional budget) for any success. If the authors’ research had taken them back further than thirty years they might have data-mined the inspiration for their bestseller-ometer, P.T. Barnam’s quote, “A sucker is born every minute.”
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This book is a must read for every serious fiction author! I'm so impressed! I have a computer screen surrounded with post it notes of every invaluable nugget to refer to as I write my supernatural thriller each day! 5 stars
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