Liz Bury 

How do you read BookVibe?

Liz Bury: A new 'book discovery' gizmo rifles through your Twitter feed to sift through others' picks. Would you recommend it?
  
  

Bookshelves
Discover anything you like? A man checks the bookshelves at Hall's bookstore, Royal Tunbridge Wells. Photograph: Sean Smith for the Guardian Photograph: Sean Smith/Guardian

A word-of-mouth recommendation is one of the most powerful ways for readers to discover new books, and now an online book discovery service, BookVibe, offers to tot up the cultural references on your Twitter feed to collate your own personal weekly list of book recommendations.

I like this idea a lot. Potentially it's actually more reliable than real word-of-mouth tips, because it's not subject to the unreliable endorsements of friends who in mad moments are suddenly gripped by the fervent belief that you're going to love that romantic novel/edgy new flash fiction sensation/serious exploration of the ageing process. And it's streets ahead of Amazon's "you liked this so you'll like …" function, because it doesn't indiscriminately assume that every book you buy is a reflection of your own reading taste.

A grand total of 3,657m new ISBNs were registered last year in the UK alone, a rise of 22% since 2009. With such a deluge of new books flooding the market every week, no wonder publishers think that lack of discoverability is the number one reason why they don't sell more books.

BookVibe is like a cross between the staff picks section in a bookshop, a word-of-mouth recommendation, and a book review section, tailored to your own specific Twitter interests.

On my list this week I'm intrigued by HhhH, "A breezily charming novel, with a thrilling story that also happens to be true, by a gifted young author amusingly anguished over the question of how to tell it," according the the Guardian review, and glad to be reminded of The Garden of Evening Mists, shortlisted for the Booker Prize in 2012 and now out in paperback.

BookVibe claims to analyse 10bn tweets to come up with its recommendations, but big data still make some mistakes: tweets about Handel's Messiah translated into a recommendation for fast-paced, gritty serial killer novel Messiah by Boris Starling. Has anyone else given it a test run? Is it working for you?

 

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