빅데이터를 이용한 패션 브랜드 평가 변화 추이 분석 : 구찌 브랜드를 중심으로

Abstract

This study empirically analyzed consumers" brand perception, assessment, and attitudes toward the Gucci fashion brand in a time series using Big Data. Specifically, a set of keywords for a period of three years—starting when the brand’s creative director was replaced—was extracted through text mining. Changes in consumers’ assessment and perceptions of the brand were analyzed empirically through opinion mining. Gucci was selected for analysis based on sales statistics for the second quarter of 2017 from British fashion magazine BoF and global fashion shopping platform Lyst. The study’s time period was divided into three groups: January 1, 2015 to December 31, 2015; January 1, 2016 to December 31, 2016;and January 1, 2017 to December 31, 2017. Text was extracted and refined based on text mining techniques. Keywords were then analyzed to identify words that represented the brand. Through the fashion data analysis platform we conducted opinion mining for one week to analyze consumers" overall evaluation of the brand. We also identified trend changes using an interest graph based on the amount of Gucci keywords that were searched, as well as the dates featuring the highest interest.