基于微博的电影首映周票房预测建模 postprint

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.