MovieTweetings: a movie rating dataset collected from twitter

Abstract

Public rating datasets, like MovieLens or Netflix, have long been popular and widely used in the recommmender systems domain for experimentation and comparison. More and more however they are becoming outdated and fail to incorporate new and relevant items. In our work, we tap into the vast availability of social media and construct a new movie rating dataset ‘MovieTweetings’ based on public and well-structured tweets. With currently over 60,000 ratings and the addition of around 500 new ratings per day we believe this dataset can show to be very useful as an always up-to-date and natural rating dataset for movie recommenders.