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Twitter, the social network service, is a rich source of information on customer response to a live event such as a television show. In this paper we present a case study where we analyzed publicly available tweets that were posted when a popular TV show was aired for the first time in a season. We use standard text-mining techniques to answer questions such as, what were the main themes during the show, what drove the popularity of the show and what were the kind of viewers who were tweeting on the show. This kind of business intelligence can be used by content producers in improving future shows, in targeted marketing to audience, in gathering competitive intelligence and many other ways.