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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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Abstract [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.
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Received: 11 September 2015
Published: 13 May 2016
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