Tracking for Manuscripts

If tracking were to be used to enhance publishing practice, I would develop a system that allowed unknown/unpublished authors a chance to make their way to the forefront. I would take data from sites like GoodReads, or, as well as other places for book reviews, such as Amazon. I would (or rather, the technology would) search for phrases like “I liked this book because…” or “the (blank) didn’t resonate with me” — descriptive phrases that gave concrete examples of what worked in the book and what didn’t. This would amass a database of certain ebbs and flows of plot, character, theme, etc. A manuscript could then be scanned into they system and the computer would search for similar ebbs and flows: Are there repeated romance themes in what is supposed to be a horror novel? Is there variety in dialog tags? How many action scenes are there? Which words get repeated the most (e.g. ‘sad’, ‘cried’, ‘whimpered’)? The program could then take that information and find comparable books and give a range of what was most successful and least successful, and why readers liked or disliked it.

This could be used in tandem with software that tracks trends in bestseller book sales. For example, if what is “in” in a particular season is dystopian young adult novels, the public might not notice a quirky, modern day love story about two tennis players. Or the audience might be tiring of the dystopian theme and be ready for it. It would all depend on timing, which a trend tracker would be able to plot. A trend tracker like this would take data from bookstores like Indigo, and (if they could get their hands on the data) Amazon.

This is not to say that the data collected and used to analyze a new manuscript would then make a guaranteed call. But the process could help unknown publishers get their books noticed a little bit more by acquisitions. It is important to note that in this hypothetical situation it would be only new authors that get put through the analyzation. As has been discussed before, a best selling author is more likely to keep producing best sellers, so they already have a better stamp of guarantee on their work, for better or worse.

The technology may always be a little bit flawed, but it just might make task of picking out the best bets in a stack of manuscripts that need more work (or that the world isn’t ready for, or has seen enough of) just a little bit easier.

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