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Goodreads wants to tell you what to read next

Library Journal calls the Netflix-like system great for book groups

By Rebekah Denn / September 19, 2011

Social media site Goodreads.com says it is better equipped than Amazon to offer truly customized book recommendations for readers.

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What book should you read next? Goodreads thinks it has some answers.

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The online site, a book-focused social network, now provides Netflix-like recommendations based on readers’ previous picks and pans. Once users have rated 20 books, the system will start suggesting new possibilities to try. The algorithm is based on one from Discoverreads, a smaller company purchased by Goodreads in March, according to Library Journal.

Computerized recommendations are a big change for a site that’s previously been about what your friends are reading and praising. The early buzz is that the change is a plus, though, and that it’s about time the site turns the data from its 6 million members into a boon for readers rather than just advertisers.

“While peer recommendations are important, it's hard to argue against math,” said Time.com. Library Journal thinks the recommendations will be a boon to book groups, always facing the question of what their members are collectively most likely to enjoy.

I gave the service a trial spin. For beginning users, it is of course a rough tool – 20 ratings was enough to give the system a good idea that I enjoyed classic children's literature, but not enough to translate that to new releases I haven’t yet encountered. I’m sure it means something that I’m among the few living readers not to appreciate Elizabeth Gilbert’s “Eat Pray Love,” but I think it’ll take Goodreads more data points to figure out just what that says about my tastes.

(The system did suggest I try Gabrielle Hamilton’s “Blood, Bones, and Butter,” a book I have already read. I was lukewarm on it at the start but loved the last third. Hard to translate that into stars.)

By relying on ratings rather than searches or purchases, Goodreads does come up with useful data. One of the shortcomings of Amazon’s system, for instance, is that my account isn’t just based on my personal likes; it’s skewed by my one-time searches for work, by my mom’s searches when she visits our house, by gift purchases, by my kids, and so on.

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