Television in India is becoming huge industry; it has thousands of programs in so many languages. Every year the small screen has been producing numerous celebrities. More than half of all Indian households own a TV. The television production industry has maintained its importance over the past few decades. The precise and timely prediction of program popularity is of great value added for content suppliers, broadcast TV operators and advertisers to get the financial gain. The predicted information can be beneficial for operators in TV program purchasing decisions and it can help advertisers to formulate reasonable advertisement investment plans. Besides this a technical matters, a precise program popularity prediction optimizes the whole broadcasting system, like the content delivery network strategy. The objective of this paper is to analyze the programmes popularity based on the people sentiments and interest for this data mining technology has been adopted. The concentrate is on points related to the user ratings of programmes, like discovering if sentimental, big-budget programmes are more popular than their low budget series of comedy, drama, games, news and sports. The analysis also predicted the relationship between whether any particular actors or actresses are likely to help a programme to succeed.
Data Minning, Text Mining, TV Show, NAnalysis Popularity
