A study on user's preferable model through the analysis of twitter based on storm

Abstract

With the rapid growing number of SNS users throughout the world, digital data has been swiftly stored up and the significance of analyzing user's opinion becomes the focus of the world's attention. As a usual, it is well known that hadoop plays a crucial role in dealing with a mass storage device like data especially in SNS twitter. However, the downside is that it cannot reflect the characteristics of SNS that change in real time. Accordingly, the purpose of this study is to analyze how twitter data change in real time and to provide an additionally applicable model to see user's preferable model regarding keywords, based on analytical storm changes. The SNS analyzing model examined in this study enhances the possibility of analyzing the frequency of using keywords as well as preference, which will certainly be efficient in many applicable fields. © 2016 International Information Institute.