Abstract
In this chapter, we focus the attention on whether text reviews of movies which are nominated for a Best Picture award carry any sign of the likelihood of a movie winning the award. We suggest that a measure of how controversial the movie is perceived to be, the value of which could be extracted by a text analysis of the reviews, is a potential predictor of a win, aside from other predictors identified in past work. This also is an opportunity to discuss text mining and sentiment analysis techniques.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bone PF. Word-of-mouth effects on short-term and long-term product judgments. J Bus Res. 1995;32(3):213–23.
Liu B. Web data mining: exploring hyperlinks, contents, and usage data. New York, NY: Springer; 2007.
O’Leary S, Shehan K. Building buzz to beat the big boys: word of mouth marketing for small businesses. Westport, CT: Praeger Publishers; 2008.
Zhang Z, Li X. Controversy in marketing: mining sentiments in social media. In: Proceedings of the 43rd Hawaii international conference on systems sciences. Washington, DC: IEEE; 2010.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Haughton, D., McLaughlin, MD., Mentzer, K., Zhang, C. (2015). Can We Predict Oscars from Twitter and Movie Review Data?. In: Movie Analytics. SpringerBriefs in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-09426-7_6
Download citation
DOI: https://doi.org/10.1007/978-3-319-09426-7_6
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09425-0
Online ISBN: 978-3-319-09426-7
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)