The brand images analysis of korean and german carsbased on big data

Abstract

This study would like to find out influential factors in brand image by SNS original data sources and then builds ontology by relative and associated words. According to previou theoretical studies and trend monitors survey, an ontology built brand image's influential factors and finds out associated brand images from car blogs, and Twitter's terms. The ontology collects original data from Twitter in Korea. By using a Korean analyzer to process, it can select key words from its original data source and then those key words make density based on K-means clustering. Korean and German cars were selected for comparison. Then, based on these process, the major six image factors are selected; image, symbol, trademark, quality, price, and country of origin. With the use of clustering analysis, the two Korean cars and two German cars' brands show different. Finally, this study found out correlations between brand image of cars and consumer's purchasing intention. © 2016 SERSC.