Book “DNA”

What might a data-driven approach towards book reading look like? We took a look at BookLamp earlier, and here’s some news from Publishing Perspectives: “BookLamp Infographic Visualizes the Thematic Flow of a Book” —

(Click on the image to the left for a large version of the book map, courtesy of Publishing Perspectives)

“ — aka the Book Genome Project — breaks a book down into 32,160 data points and quantifies everything from density and pacing, all in aid of book discovery. Now the team of razor-sharp engineers have put their skills to the test in putting together a visual infographic of thematic flow of a book.”

Presumably, this sort of thing gives readers a rather unique perspective of books that they are reading, or have read, or want to read. I’m still not crazy about the actual visual representation itself, but the idea of being able to visual a book’s content by thematic flow is pretty nifty — and lots of credit to them for an impressive amount of work that has gone into the BookLamp project so far.

How exactly does this work? Publishing Perspectives has a bit more on the inner workings (“Is BookLamp’s “Book Genome Project” the Future of Discovery?”)

“We do this by taking the full text provided by a publisher in a digital format and running it though our computer,” explains CEO Aaron Stanton. “Our program breaks a book up into 100 scenes and measures the ‘DNA’ of each scene, looking for 132 different thematic ingredients, and another 2,000 variables.”

Can a computer really ‘read’ a book as well as a human being?

“Stanton thinks so. “Our original models are based on focus groups,” he says. “We would give them a highly dense scene and a low density scene, for example, and ask them to assess them, which gave us a basis for training the models. Then we looked at books that might exceed the models and tweaked the formulas. In this way, our algorithms are trained like a human being.”


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I run the ThinkLab at the University of Cambridge, and research digital habits, productivity, and wellbeing.

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