The text mining and classification analyses on the relationship of Macau special administrative region's policy addresses from 2012 to 2013

Abstract

The study aimed at analyzing the keywords of the Macau Special Administrative Region's 2012 and 2013 annual policy addresses. The contribution of the study included the following two points. First, the study used the text mining method in order to explore the content of policy address. Second, the study applied the SVM (Support Vector Machine) and random forests classification analysis to explore the relationship of the keywords between the two years' policy addresses.