DocumentCode
1867777
Title
Improving Movie Gross Prediction through News Analysis
Author
Zhang, Wenbin ; Skiena, Steven
Volume
1
fYear
2009
fDate
15-18 Sept. 2009
Firstpage
301
Lastpage
304
Abstract
Traditional movie gross predictions are based on numerical and categorical movie data from The Internet Movie Database (IMDB). In this paper, we use the quantitative news data generated by Lydia, our system for large-scale news analysis, to help people to predict movie grosses. By analyzing two different models (regression and k-nearest neighbor models), we find models using only news data can achieve similar performance to those using IMDB data. Moreover, we can achieve better performance by using the combination of IMDB data and news data. Further, the improvement is statistically significant.
Keywords
Computer science; Conferences; Deductive databases; Economic forecasting; Intelligent agent; Internet; Motion pictures; Predictive models; Thumb; USA Councils; Financial Modeling; Movie Gross Prediction; News Analysis; Sentiment Analysis;
fLanguage
English
Publisher
iet
Conference_Titel
Web Intelligence and Intelligent Agent Technologies, 2009. WI-IAT '09. IEEE/WIC/ACM International Joint Conferences on
Conference_Location
Milan, Italy
Print_ISBN
978-0-7695-3801-3
Electronic_ISBN
978-1-4244-5331-3
Type
conf
DOI
10.1109/WI-IAT.2009.53
Filename
5286056
Link To Document