By November 26, 2008 2 Comments Read More →

The Art & Science of Recommendations: the Brad Pitt Factor

The New York Times had a recent interesting article: If You Like This, You’re Sure to Like That by Clive Thompson. The article examines the difficulty of using a computer program, such as NetFlix’s Cinematch, to create recommendation lists. I admit an addiction to clicking through my Amazon and iTunes recommendations, ofter lured into wildly off-base purchases.

Audiobook recommendations add another layer of complexity. The false assumption of good book=good audiobook may lead listeners to selections where a lackluster narrator effectively kills a title. Read Me a Story, Brad Pitt: When Audiobook Casting Goes Terribly Wrong by Nate DiMeo, posted on Slate.com, is a must-read. Then give a listen to NPR’s “When Audio Books Jar the Ear” where you can hear Brad’s perfectly dreadful Spanish accent! I especially like a quote from Thompson’s NYT article, “It used to be that if you wanted to buy a book, rent a movie or shop for some music, you had to rely on flesh-and-blood judgment — yours, or that of someone you trusted.”

Call me old fashioned, but that’s where librarians beat computerized recommendations every time: nothing is better than getting the right audiobook into the right hands. When a sixth-grader who has not read a book all year came running into my school library yesterday after finishing Star Wars: The Way of the Appentice, and asked for another great STORY, I had a listener sold on literature, not audiobooks. I had to smile when I realized that the narrator of that audiobook was Jonathan Davis, highlighed in a recent post!

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Mary Burkey is a National Board Certified teacher-librarian in the Olentangy School District in Columbus, Ohio.

2 Comments on "The Art & Science of Recommendations: the Brad Pitt Factor"

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  1. Keir says:

    Great post and great links. The NYT Magazine article was fascinating, but I came to a similar conclusion as you did. And when we designed Booklist Online, we built it around the premise that algorithms are no substitute for human experience–our recommendations are made by editors!

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