Books, the idea: Here’s comes the data; what to do with it?

As you may know, Amazon is now compiling and making available to the public information about the “most highlighted” books among Kindle users, and even the “most highlighted” passages. A Dan Brown book, the Bible, and a book I’ve never heard of called The Shack are the top three most-highlighted works as I type this. In general, the books on that list are religious/spiritual titles; self-help stuff; business-advice books; or some combination of those categories. This is not exactly a surprise, but it’s interesting to see.

It’s more interesting to parse the most highlighted passages, which you can do here. Below the jump, I’ve listed the top ten passages (as of the moment when I’m typing this), without naming the authors or books. I think it’s more fun to read them without that context. And also to wonder about the people who did the highlighting. Perhaps, inspired by David Shields, someone could build an essay, or even a whole book, out of these mostly platitudinous word clusters.

That’s a joke (sort of). But of course this is just the sort of techno-driven development in reading/books that has, in a sense, inspired this entire series. As many have noted:

  • books are containers of readable information or stories and so on
  • but also: books are display objects (on shelves, or simply being read in public)

Earlier I suggested that if  books are going to migrate into digital-only form in time, then perhaps people will need a flat-screen “shelf” that displays the digital spines of whatever we’re reading — or want people to think we’re reading.

I’m not completely serious about this stuff … but I’m not completely kidding. What could be done with the information that Amazon is gathering from Kindle users? Possibly your favorite highlighted passages could be a screensaver or something? Or run a as a kind of news ticker beneath the digital renderings of bookspines or the virtual shelving unit described above?

Anyway. Here are those top highlighted passages. See what you make of them: Read more

The idea of the book, cont’d: Trophy books revealed

Core77 points to Music Machinery’s suggestion that Amazon could do a lot more with the data it is collecting (or could be collecting) via Kindle software: “It keeps track of where you are in a book so that if you switch devices (from an iPhone to a Kindle or an iPad or desktop), you can pick up exactly where you left off.” This leads Music Machinery to suggest the generation of LastFM-style charts and so on, identifying various trends about how we read and so on. The suggestion that jumped out at me:

Trophy Books – books that are most frequently purchased, but never actually read.

I’m not personally excited about user-data-harvesting, but that is, in fact, pretty interesting. And funny.

Surely if such information does end up being collected, it could be cross-worked with book-imagery that we may one day display on our devices and virtual shelves?

See the Music Machinery post for more of Paul Lemere’s ideas. Earlier posts in this occasional Murketing series are here.

In NYT Book Review: The Numerati

As mentioned in the comments to this earlier post*, I reviewed The Numerati by Stephen Baker. That review is out, in tomorrow’s NYT Book Review section — first review I’ve done for them in years, though I used to write for them a lot. Anyway, it starts like this:

Maybe you’re the kind of person who doesn’t believe that the kind of person you are can be deduced by an algorithm and expressed through shorthand categorizations like “urban youth” or “hearth keeper.” Maybe I’d agree with you, and maybe we’re right. But the kind of people — “crack mathematicians, computer scientists and engineers” — whom Stephen Baker writes about in “The Numerati” clearly see things differently. In fact, they probably regard such skepticism as more fodder for the math-driven identity formulas they’ve created to satisfy the consumer-product companies and politicians who hire them….

Here’s the link.

[* Note: The review was already written and filed prior to that post, if that matters to you at all.]

Data-mining moment of the week?

The other day I was reading some random news story on a newspaper site — I think a Philadelphia paper,  and the article was something about the McCain campaign.

At the bottom was this:

I’m interested in the stuff at right. People who read this article also bought a Movado watch? Or a portable DVD player? Really? How many people? And how is that useful information?

Put that in your algorithm

Recently I read Stephen Baker’s book The Numerati, all about “the mathematical modeling of humanity,” and Bob Garfield’s long ode to data mining in Ad Age, which strikes very similar themes about the power of algorithms.

More recently I listened to a 60 Minutes report about the recent troubles on Wall Street and beyond (via podcast). Here’s a bit taken from the news show’s online textual recap of that segment:

These complex financial instruments were actually designed by mathematicians and physicists, who used algorithms and computer models to reconstitute the unreliable loans in a way that was supposed to eliminate most of the risk.

“Obviously they turned out to be wrong,” Partnoy says. [Frank Partnoy, a former derivatives broker and corporate securities attorney, who now teaches law at the University of San Diego.]

Asked why, he says, “Because you can’t model human behavior with math.”

Hm.

What say you? Can human behavior be mathematically modeled, or not?