International Journal on Advanced Science, Engineering and Information Technology, Vol. 11 (2021) No. 1, pages: 51-56, DOI:10.18517/ijaseit.11.1.14078

Study on Automobile Culture of Developed and Emerging Countries in Asia Using Text Mining Analysis on Social Media

Yongho Joo, Gilsang Yoo


To be successful in the automobile export business, it is essential to accurately identify consumer preferences in developed and emerging countries. In this study, big data were collected and compared using NodeXL to verify differences in automotive preferences caused by differences in living standards, regional characteristics and culture, and related regulations and policies between developed and emerging countries in Asia. The data to be analyzed were collected from Twitter big data on major Asian and emerging countries and cleaned up, and text mining techniques were applied for frequency analysis. Based on this, we predicted the demand for automobiles in emerging countries in the future and derived a way for automakers to efficiently approach the automobile markets of emerging countries. The analysis results are as follows: First, emerging economies are very fond of foreign vehicles that value their confidence and pride but are more price-sensitive and prefer medium-to-small car sedans rather than SUVs. Second, pride and price should be the first marketing considerations when an automotive business enters an emerging country. Third, in emerging economies, if small- and medium-sized cars that fit lower prices are marketed mainly as sedans rather than as SUVs, local consumers will respond well. This study's results are expected to be used as primary data for the localization sales factors necessary in understanding the car preferences of different countries for overseas marketing.


NodeXL; term frequency; text mining; auto industry; comparative analysis; marketing.

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