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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References
Asur, S., Huberman, B.A.: Predicting the future with social media. CoRR, abs/1003.5699 (2010)
Fox, J.: Applied Regression Analysis, Linear Models, and Related Methods. SAGE Publications (February 1997)
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA data mining software: an update. SIGKDD 11, 10–18 (2009)
Joshi, M., Das, D., Gimpel, K., Smith, N.A.: Movie reviews and revenues: An experiment in text regression. In: Proceedings of NAACL-HLT (2010)
Mishne, G., de Rijke, M.: Capturing global mood levels using blog posts. In: AAAI-CAAW 2006, pp. 145–152 (2006)
Tsagkias, E., de Rijke, M., Weerkamp, W.: Predicting the volume of comments on online news stories. In: CIKM 2009, Hong Kong, pp. 1765–1768. ACM (2009)
Tsagkias, M., Weerkamp, W., de Rijke, M.: News Comments: Exploring, Modeling, and Online Prediction. In: Gurrin, C., He, Y., Kazai, G., Kruschwitz, U., Little, S., Roelleke, T., Rüger, S., van Rijsbergen, K. (eds.) ECIR 2010. LNCS, vol. 5993, pp. 191–203. Springer, Heidelberg (2010)
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Oghina, A., Breuss, M., Tsagkias, M., de Rijke, M. (2012). Predicting IMDB Movie Ratings Using Social Media. In: Baeza-Yates, R., et al. Advances in Information Retrieval. ECIR 2012. Lecture Notes in Computer Science, vol 7224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28997-2_51
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DOI: https://doi.org/10.1007/978-3-642-28997-2_51
Publisher Name: Springer, Berlin, Heidelberg
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