Internet Public Opinion Analysis Based on Apriori Association Rule Mining
Xinjie Hu, Zhanji Wei · 2019
This paper introduces the Internet Public Opinion (IPO), its occurrence, development and the current situation. Along with the rapid development of the internet and the exponential growth of mobile internet users, the internet environment has become the center and platform for public opinion expression, information transmission, emotion release and participation of national public affairs. IPO has therefore developing rapidly as well. This paper investigated the possibility of applying Association Rule Mining (ARM) for the analysis of IPO, including the standards (support, confidence, and lift) of ARM in IPO, analyzed the Pros and Cons over association rule Apriori Algorithm, Partition Algorithm, DHP Algorithm. Given the Apriori Algorithm mining IPO information and association, the analysis procedures and experimental verification, the Apriori Algorithm applied for ARM can evidently achieve IPO analysis and provide prediction with solutions.