Looking for new books to add to your summer reading list? You probably already know to check sources like Goodreads and the New York Times book reviews, but that’s not always enough. Here are a few of my favorite non-obvious sources for online book recommendations.
Shelf Awareness for Readers
This free, twice-weekly email newsletter from book trade publication Shelf Awareness launched in 2011 and is still one of my favorite places to learn about new books. The newsletter comes out on Tuesdays and Fridays (or you can read it online) and in each issue, independent booksellers and reviewers recommend 25 books that have just hit stores. While some bestsellers from big authors are included, plenty of books from small presses and debut authors are also included, making this a good place to learn about books you probably wouldn’t have heard of otherwise.
Publishers Lunch Bookateria
Bookateria, which launched in December 2012, is the place to go if you love best-of lists: The site, from book publishing database/newsletter/website Publishers Marketplace, corrals tons of best-of, bestseller and featured book lists into one site — so you can scan lists like Amazon’s Best Books of August 2013, this year’s Edgar Award-winning mysteries and the New York Times best books of the year all in one place. Bookateria also flags the latest releases in a wide variety of genres, and has a section devoted to books in the news. Affiliate links to a number of readers let you buy books from the site.
BookLamp and Bookish
Both of these sites offer book recommendations based on algorithms. BookLamp analyzes a book’s “DNA” — breaking its text down into points like characters and language — to offer recommendations based on books and authors you already like. Bookish, the website backed by Simon & Schuster, HarperCollins and Hachette that launched in February, looks at some different factors: As I wrote when it launched, it “The recommendation looks at features like the authors, editors and illustrators who contributed to a book, the awards a book has won, and genre and publication date, then layers on a machine-learning component that parses user and professional reviews to try to distill themes, concepts and sentiments. Insights from the editorial team are included, too.”
Neither of these sites is perfect, and both are limited by the fact that they don’t work with every book you type in. Bookish’s recommendation engine currently works with 320,009 books (up from about 250,000 in February). BookLamp doesn’t share the number of books it analyzes for “DNA,” but it’s working with only a limited number of publishers: Random House and HarperCollins titles are included, for instance, but not Simon & Schuster or Penguin titles. Nonetheless, both sites are worth testing out, and I was often happily surprised by the non-obvious recommendations they offered.
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