Social media has become widespread and essential for social networking and content - based distribution in recent years. However, the information created by these websites remains mostly unexplored. We show how social content delivery material may be utilized to predict real-world consequences in this article. We utilize Twitter.com buzz to predict box-office revenues for movies. We show that a simple model based on the rate at which tweets regarding certain subjects are generated may beat market-based predictions. We also show how emotions collected from Twitter may be used to enhance social media's predicting capability. We look at the problem of forecasting box-office sales for movies using Twitter buzz, which is one of the Internet's fastest growing social networks. We chose movies as the subject of our research for two primary reasons, which are described in this article.