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Recommendation systems are important intelligent systems that play a vitalrole in providing selective information to users. Traditional approaches inrecommendation systems include collaborative filtering and content-basedfiltering. However, these approaches have certain limitations like thenecessity of prior user history and habits for performing the task ofrecommendation. In order to reduce the effect of such dependencies, this paperproposes a hybrid recommendation system which combines the collaborativefiltering, content-based filtering with sentiment analysis of movie tweets. Themovie tweets have been collected from microblogging websites to understand thecurrent trends and user response of the movie. Experiments conducted on publicdatabase produce promising results.

Movie Recommendation System using Sentiment Analysis from Microblogging Data