Real-time Analysis of Citizens’ Reactions to Election Campaign Scenes Using Inverse Order Tree and Smartphone Application

Abstract

In this era of smart information and communications, the amount of data increases geometrically. Locating and analyzing data and their conditions real-time has emerged as an important factor for prompt data processing. In this study, an inverse order tree structure that inversely generates existing tree structures to help understand the local location and local features of big data was designed, and a mathematical model was completed. An experiment was performed with a smartphone application that analyzes and quantifies emotional data containing citizens' emotional reactions to the campaigning scenes of Gwangju Metropolitan City's mayoral election in Korea. In the experiment, the data collection agents quantified local emotional data for the campaign scenes of two leading mayoral candidates. Using the inverse order tree structure, we collected the data in real time, which were applied to one of the candidates' campaign. This study is very meaningful because for the first time, smartphones were used for analyzing the approval ratings of the candidates during electoral campaigning, and emotional data were quantified and analyzed.