Television has become a region of everyone‟s life. TV Reality shows unit increasing day-by-day among the gift generations. TV Rating purpose (TRP) could be a tool provided to evaluate that programs area unit viewed the foremost.TV series constitute a sun rising sector of the business region. This provides America folks selection and conjointly the actual channel quality. This gives us people choice and also the particular channel popularity. Since we can performance prediction permits a broadcasting network to higher specialize in the substantial investment required for his or her construction. However, our existing prediction methods are only used to predict the popular show by the TRP calculation and the accuracy poor prediction programs that have a poor popularity point. This paper describes our advanced prediction model defines the performance analysis of the popular show which includes finding the factors that are leading the show into a success. First, finding the topmost 20 popular shows in the IMDb page using rating prediction. Then, fetching the information of each episode reviews. CNN-text classification algorithm is applied to predict the grade based review of each show depending on the episode or rating based prediction. According to this, find out the factors that are used to predict the show as popular. The predictors of appreciation and popularity of shows are considered as Awards, Nominations, Characters, Soundtracks, Parental Guidance, Grade Classification and Overall rating. This data will be helpful for operators in television program buying choices and may facilitate advertisers to formulate cheap advertisement investment plans. The graph depicts the predictors of appreciation and popularity of each show in the form of a pie chart and histogram etc.
Volume 12 | 07-Special Issue
Pages: 1541-1550
DOI: 10.5373/JARDCS/V12SP7/20202257