The Value of Social (for) TV
summary
Claims that public social data predicts viewership and ad impact using real Twitter handles, Experian/Facebook demographics and GetGlue/Biggle check-ins. Builds recommendation systems from follower tweets and networks, predicts Nielsen and customer lifetime value, and measures time-shifting per user. Finds a projected market of 256 billion, ad examples from Super Bowl show peaky vs sustained buzz (Teleflora spike, Chevy sustained game), and consistent gendered retweeting where women retweet women more; running a Mass Relevance field experiment to test causal effects.
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