Parakweet Launches BookVibe Recommendations

May 17, 2013 

Parakweet Inc. today announces the launch of BookVibe, a social graph-powered, personalized book recommendation engine.

Never miss a book tip from your Twitter friends again! BookVibe shows you the books that your friends on Twitter are discussing, generating a real-time and personalized book stream just for you. As examples, check out the book streams of noted Venture Capitalist and startup book author, Brad Feld: http://www.bookvibe.com/people/bfeld and leading author, Neil Gaiman: http://www.bookvibe.com/people/neilhimself

You can also use BookVibe to peek into the book streams of friends and competitors.  Simply visit www.bookvibe.com and enter a Twitter handle to see their live book stream.

How it works: The Parakweet platform is able to extract meaning from unstructured social chatter.

Using a proprietary Natural Language Processing based platform, Parakweet is able to extract conversations where customers are discussing products such as books, along with associated metadata such as intent, behaviors (“read”, “recommend”), and sentiment, with unprecedented accuracy.

How big is the haystack?

Twitter users send more than 400 million tweets a day. In the case of books, Parakweet identifies approximately 100,000 tweets a day that are actually about books with 96% precision. Keyword-based search techniques would identify approximately 10 million tweets per day that could be book titles, with around 99% false positives or “noise.” By maximizing the signal-to-noise ratio, Parakweet enables complex and nuanced operations to be performed based on the accurately identified entities.

How do we make money?

The BookVibe service is free to consumers.  Parakweet uses the same technology platform to provide paid analytics services to media companies, enabling them to tap into these micro-reviews and other social signals that consumers are generating organically in the social universe. All Parakweet products are available through APIs which enable integration into other platforms as well as the combination of Social Media Metadata with customers’ proprietary internal data.

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