Abstract:
This project developed the models to predict the success and the ratings of a
new movie before its release. Since the success of a movie is highly influenced by the
actor, actress, director, music director and production company, those historical data
were extracted from the Internet Movie Database (IMDb).The Box Office Mojo stores
information about the cost of production of a movie and the total income of the movie.
This information is helpful to determine whether the movie is successful or not in terms
of revenue. A threshold was defined on revenue based on heuristics to categorize the
movie into success or failure. Teasers’ and trailers’ comments were extracted from
YouTube as those are very helpful to rate a movie. The keywords were extracted from
the user reviews using a Natural Language Processing (NLP) technique and those
reviews were categorized into positive or negative based on the sentimental analysis. A
Random Forest Algorithm was trained using the features extracted from IMDb to predict
the success of a movie. Further, the Naive Bayers model was trained using the user
reviews extracted from YouTube to predict the rating of a movie. The models were tested
on real datasets and the accuracy of those were evaluated respectively. Finally, two
conclusions have been met that the rating of a new movie cannot be predicted in advance
through the YouTube trailers’ and teasers’ comments and the success of a new movie
can be predicted in advance by using the data or features collected from online. The
performances of the models are decent enough compared to the existing models in the
literature. The Success Prediction model can be used as an early assessment tool of
movies since it has gained 70% overall accuracy and hence, useful for the people in the
movie industry and the audience of the movies. YouTube allows to extract a limited
number of user comments and hence, this factor could be negatively affected on the
accuracy of the movie rating prediction. This abstract was presented at International
Research Conference of Uva Wellassa University of Sri Lanka(IRCUWU2020).
