Rating predictor for shows on web based platform - M.Uma Devi, AyushSrivastava, Vaibhav Pawar (International Journal of Advanced Science and Technology, 2020)
The broad range of entertainment shows streaming over various web based platforms are rated by viewers based on their personal experience, hence providing an introspect to other viewers who have not watched the show. The proposed work aims to predict an optimal rating for an upcoming show based on various static parameters associated with the show. The proposed prediction model will take in data from all kinds of series from every corner of the world that are available and registered in Internet Movie Database (IMDB).This will help the viewers to gain an insight on the show and aid their decision of whether or not to watch the show by making use of multiple regression model of predictive analytics. The result of the proposed work is a general indicator of the show’s mathematically calculated ratings. These ratings are a factor of comparison with the total viewership at that day and time throughout a country or a wider geographical area. The proposed work is hence, aimed to have a good efficiency and to predict a near accurate rating.