소셜 빅데이터를 이용한 한국내의 대만음식 트렌드 분석 : 블로그 텍스트 분석을 중심으로

The purpose of this study is to analyze the trend of Taiwanese food in Korea using text mining analysis among social big data for blogs of representative portal site in Korea, and analyzed annual trends from 2015 to 2019.  The frequency was analyzed by the collected data set of blogs searched for 'Taiwanese food', and 'Taiwan', 'Travel', and 'Food' were maintained high frequency steadily in the first ranking group. The main attribute of Taiwanese food is 'street food in the night market' as well. Since then, food-related words such as 'famous place for visit', 'local restaurants', 'tasty' and 'recommendation' have been frequently found in the second ranking group. Specific Taiwanese food appeared, especially 'Beef noodle', 'Mango bingsu(snow flakes with syrup)', 'Bubble tea', 'Taiwanese pancake', and 'Zippie(flat fried chicken) ' were recognized as the representative Taiwanese foods in Korea. These findings are expected to be valuable information for entering the Korean food market, which emphasizes the value for money and shows preferences for snack foods or sweet desserts.