34th European Conference on IR Research, ECIR 2012, Barcelona, Spain, April 1-5, 2012: proceedings
ISBN
9783642289965
ISBN (electronic)
9783642289972
Series
Lecture Notes in Computer Science
Event
34th European Conference on Information Retrieval (ECIR 2012)
Pages (from-to)
503-507
Publisher
Heidelberg: Springer
Organisations
Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract
We predict IMDb movie ratings and consider two sets of features: surface and textual features. For the latter, we assume that no social media signal is isolated and use data from multiple channels that are linked to a particular movie, such as tweets from Twitter and comments from YouTube. We extract textual features from each channel to use in our prediction model and we explore whether data from either of these channels can help to extract a better set of textual feature for prediction. Our best performing model is able to rate movies very close to the observed values.
