Monday, August 3, 2015

You Might Also Like….


Book recommendations for people we don’t know well can be tricky. When we recommend books to friends, we have a lot of information to go on. We know their likes and dislikes, political and religious beliefs, family histories. We’ve discussed books, so we know their favorites, right down to their favorite parts (that part with the butterflies!) and, more importantly, their least favorite parts (that scene in the bathtub!).

Book recommendations are part of my library job, a very enjoyable part. But making book recommendations is one of those things that, like figure skating, looks easy until you try to do it.  A good Book Whisperer’s skill is honed by years of practice and reading.

It’s also necessary to listen for the nuances of a reader’s request. For example, when a lady asks for a “nice book” I know that’s code for no sex, violence, or upsetting elements. That hardly means a trite or uneventful read, as fans of Maeve Binchy, Joanna Trollope, or Alexander McCall Smith know well.

Recommendations for kids call for even more nuance. In just a few moments, I must get a feel for the kid (dragged in or enthusiastic), chat with him or her enough to get a feel for reading level and interests, and very delicately, balance the parent’s opinions and family standards (“No vampire books!”)

That’s why I’m dismayed by the addition of a new feature to our library’s catalog. Now appearing under the usual information about library holdings is a You Might Also Like selection of books generated by Goodreads. I have nothing against Goodreads or other computerized book recommenders. Their crowd-sourced suggestions are often good, but sometimes hit or miss. Lately the misses have outnumbered the hits.

Yesterday, I checked the library catalog for my blog mate Linda Rodriguez’s novel Every Last Secret, winner of the Malice Domestic Best First Traditional Mystery. It’s a compelling novel about “Skeet” Bannion, a half-Cherokee woman who makes a new life for herself as chief of a Missouri campus police force. The software suggested some other novels I might like based on my interest in Linda’s traditional mystery.

                     


First was Steven F. Havill’s series set in Posadas County, New Mexico featuring a female sheriff protagonist. Good match.

Another featured read alike? Stieg Larsson’s The Girl With the Dragon Tattoo, which I seem to remember was set in Sweden. Sure, TGWTD is compelling, but its blend of sex and violence hardly makes it a traditional mystery. That comparison isn’t apples to oranges; it’s apples to flamethrowers.

I am not saying these recommendations are not often useful – they are in many cases. It’s just that when they go wrong, they can go really wrong, especially for kids.

A young reader wanted the latest of Rick Riordan’s grade school fantasy novels. When I checked the You Might Like section, books by Lori Armstrong came up. The first of her books in the list? Bitten, an adult vampire novel.  If you scrolled down the listings, you’d find another of her books, one that was written for children, but the way the computer program worked, Armstrong’s most recent titles were listed at the top. And kids don’t scroll. Children have a more trusting relationship with computers than adults do. Adults have an easier time determining when to trust and when not to trust what a computer “tells” us. Kids, the digital natives who have grown up in the blue light of a computer screen, sometimes lack this ability.

A coworker shared a story about a little girl who searched the catalog for what I’ll call Book X. The girl kept saying “but I don’t want to read Book Y.” We checked the computer screen. She thought that because her book was not available, she had to take the next book the computer listed in the You Might Like section.

Until book-matching software improves, I might like it better if libraries stopped using crowd-sourced book recommendations.

Writers, have you been pleased with the titles that book recommendation sites like Goodreads match to your book?


17 comments:

  1. I am old fashioned and ignore all computer or crowd-sourced recommendations – even while I hope people can find my Seamus McCree series through those sources. Talk about conflicted.

    I rely on individual people I trust. I know it is old-fashioned, but there it is.

    ~ Jim

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  2. I have to admit I pretty much ignore the suggestions that computers produce for reading. Most of the time, I have a specific book in mind before I start looking. And I have such a long TBR list that I'm never looking for books to add to it.

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  3. Between the Washington Post and NYT book reviews, my weekly email from Murder by the Book in Houston, and the new book publicity on the blogs, my hold list in the library system is crammed. Sometimes I resort to the "freeze" designation so I don't lose my place and have time to read the book.

    I remember trying to find books for my 12 year old son to read, before the explosion of YA books. Nothing appealed, until he discovered the Harlan Coben series about Myron Bolitar. The pleasure of introducing a new author to a reluctant reader? Unsurpassed.

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  4. I have to admit that both Goodreads and Amazon tend to recommend books I have already read! I guess that means they are good at predicting my likes/dislikes. What they don't account for though are books from other genres that I might like. I often learn of new books from blogs and add them to my TBR. For some reason neither Amazon nor Goodreads seems to pick up on these 'out of character' selections and follow through with them. For some perverse reason, with notable exceptions, I don't tend to care for the mainstream must reads. Maybe because I prefer the path not taken in reading, and in life!

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  5. Hi Jim - I guess I'm old fashioned, too!

    KM - I'm with you. Somehow, by some kind of book osmosis, my TBR just grows. It's a combination of so many things I've managed to hear and read about, but I can honestly say I'm rarely persuaded to try a book recommended by an algorithm.

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  6. Margaret - You are right - It is a great feeling to introduce a young reader to that perfect book! And Coben's Mickey Bolitar (Myron's nephew) series has turned many a reluctant reader into a voracious reader, too.

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  7. Kait, I think I am with you on that "Path not taken" in reading. I'm open to so many new things - poetry, literary fiction, graphic novels. Just give me a great story! Just don't give me the same old, same old, which is what I think Amazon is good at - just giving me more of the same.

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  8. A related complaint from a fellow county library user: I will click through to get more information on a book. I'll be reading the list of copies, how many there are, which libraries they are at, etc. And while I'm reading, the darn "books you might also like" information will pop on the middle of my screen, as if I must be more interested in that than in what I WAS ALREADY READING. If they have to/want to provide this information, let it fill at the bottom of the screen, below the information people might already be reading. Don't interrupt the information people actually clicked over to see.

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  9. Barb - I am totally with you on this! May I share this observation with the powers that be?

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  10. After I place an order for books on Amazon, often used books from different sources since there are no book stores near me.so I usually order at least 5 or 6 books on my TBR list. Within a day or two I get all these suggestions for books I might like. Even more annoying is they want me to rate the books I ordered, some I haven't even received yet, and no way would I have had the time to read even one of the books yet. Maybe some people have time to read a book a day, but I'm not one of them.

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  11. When I recently searched for How to Write a Damn Good Mystery by James Frey on my library's computer, it suggested I might also like a book about the lost art of letter writing. Interesting, but not quite on target. I rarely read books recommended by a computer algorithm.

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  12. Hi Gloria,
    I am with you! I love the speed of my Amazon purchases, but the "suggestions" and requests for ratings feels like badgering sometimes.

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  13. Kara, it's those wonky suggestions that just send me around the bend.

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  14. Great article, Shari. I have to be careful while in bookstores or libraries. I get so enthusiastic about some books that I point them out to people standing around me. They get recommendations, whether they asked for them or not.

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  15. Very interesting, Shari. I've occasionally found a new series through these kind of recommendations. Just out of curiosity, I looked up Tagged for Death and Fairfax County recommended a bunch of other cozy mysteries. I also noticed they had an explanation for why they recommended them.

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  16. Hi Grace, Spread the love!

    Hi Sherry, I have seen some great matches with Goodreads. That's why the clunkers are so, well, clunky. I think the software will get better - eventually.

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