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Goodreads is better for showing me my friends’ opinions on books, and Library Thing is lightyears better for capturing data on my library.Goodreads has been good about adding features, which has improved the site experience for me and captured more information, but they’re still far behind LT, and I really wonder if they should try to catch up.Goodreads is free and runs on ad revenue, whereas Library Thing is ad-free and free up to 200 books, after which you are asked to pay /year or for a lifetime membership.
If I had to choose a word to sum up each, I’d call Goodreads “simple” and Library Thing “robust.” Goodreads’ interface is clean, appealing and fairly self-explanatory, and the conceits of social networking have been widely disseminated, so the bar to new user entry is low.
Library Thing can be more intimidating, its wealth of information necessitating and populating many fields all over the screen. Unlike Goodreads, which is committed to a categorization system called ‘shelves’, Library Thing uses tagging.
On Goodreads, book cover is linked to -linked Amazon images.
Library Thing has a great book-adding interface that allows you to type the tags once for one group of book-adds and integrates a barcode scanner seamlessly.
I thought it was time to revisit the topic and really dig into the pros and cons of the two sites.
Now, I do realize there are other book-cataloging websites – many.
That gives you the basic difference between the sites in a nutshell: GR is centered on the social aspects, LT is centered on your books.
Still, it’s more than possible to use them in a very similar way.
They have a versatile batch-edit mode for changes, and you can search hundreds of libraries worldwide as well as Amazon, whereas Goodreads only searches the various Amazon sites.
If I’m going to spend time entering data on my books, I prefer to have complete and accurate information, so Library Thing wins by a mile on that front.
It is fun to explore other people’s book collections, see library similarities and see the trends and recommendations that so much data produce.