Pre-release prediction of crowd opinion on movies by label distribution learning
Xin Geng, Peng Hou · 2015
This paper studies an interesting problem: is it pos-sible to predict the crowd opinion about a movie before the movie is actually released? The crowd opinion is here expressed by the distribution of rat-ings given by a sufficient amount of people. Con-sequently, the pre-release crowd opinion predic-tion can be regarded as a Label Distribution Learn-ing (LDL) problem. In order to solve this prob-lem, a Label Distribution Support Vector Regressor (LDSVR) is proposed in this paper. The basic idea of LDSVR is to fit a sigmoid function to each com-ponent of the label distribution simultaneously by a multi-output support vector machine. Experimen-tal results show that LDSVR can accurately pre-dict peoples’s rating distribution about a movie just based on the pre-release metadata of the movie. 1