Predicting IMDB Movie Ratings Using Social Media

  • Andrei Oghina
  • Mathias Breuss
  • Manos Tsagkias
  • Maarten de Rijke
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7224)

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Andrei Oghina
    • 1
  • Mathias Breuss
    • 1
  • Manos Tsagkias
    • 1
  • Maarten de Rijke
    • 1
  1. 1.ISLAUniversity of AmsterdamAmsterdamThe Netherlands

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