Predicting Movie Genre Preferences from Personality and Values of Social Media Users
We propose a novel technique to predict a user’s movie genre preference from her psycholinguistic attributes obtained from user social media interactions. In particular, we build machine learning based classiﬁcation models that take user tweets as input to derive her psychological attributes: personality and value scores, and gives her movie genre preference as output. We train these models using user tweets in Twitter, and her reviews and ratings of movies of different genres in Internet movie database (IMDb). We exploit a key concept of psychology, i.e., an individual’s personality and values may inﬂuence her choice in performing different actions in real life. We have investigated how personality and values independently and collectively inﬂuence a user preference on different movie genres. Our proposed model can be used for recommending movies to social media users.