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New Technology of Library and Information Service  2016, Vol. 32 Issue (4): 31-39    DOI: 10.11925/infotech.1003-3513.2016.04.04
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Predicting Opening Weekend Box Office Prediction Based on Microblog
Wang Xiaoyun,Yuan Yuan(),Shi Lingling
Management School, Hangzhou Dianzi University, Hangzhou 310012, China
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[Objective] This study aims to solve the problems of the existing pre-release box office prediction models due to data constraints and other factors. [Methods] We first retrieved microblog comments, and then used SVM to identify explicit consumer intention, namely strong positive comments. Second, we modified the traditional sentiment classification schemes to build a Chinese microblog sentiment dictionary based on HowNet. Finally, we defined a new user influence feature and used the BP neural network to predict box office. [Results] The proposed model could forecast the opening box office more accuately. [Limitations] Due to inadequate corpus, the sentiment dictionary may not work well for all microblog movie comments. A dynamic forecasting model was not established between the pre-release and post-release period. [Conclusions] The proposed model can effectively predict opening box office.

Key wordsSentiment dictionary      Sentiment classification      Opening weekend box office prediction      Neural network     
Received: 11 September 2015      Published: 13 May 2016

Cite this article:

Wang Xiaoyun,Yuan Yuan,Shi Lingling. Predicting Opening Weekend Box Office Prediction Based on Microblog. New Technology of Library and Information Service, 2016, 32(4): 31-39.

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