Analysis of Youth’s Sustainable Fashion Consumption Trends using Text Mining

The purpose of this study is to identify trends in youth fashion consumption that exist throughout society by analyzing big data on youth's sustainable fashion consumption in order to propose learning contents for home economics education. The research method is big data analysis. Naver, Daum, Google, YouTube, and Twitter were analyzed to identify the top 50 major keywords in big data on youth's sustainable fashion consumption using text mining techniques. Then, four clusters were created and visualized through CONCOR analysis, Cluster Diagram, and NetDraw. Looking at the results, the main keywords for youth's sustainable fashion consumption are ‘brand’, ‘consumer’, ‘environment’, ‘eco-friendly’, ‘product’, ‘trend’, ‘education’, ‘society’, ‘company’, It was confirmed that ‘daily life’ was a keyword that appeared in the top 10 and that both frequency and importance were high. In addition, as keywords such as ‘online’, ‘platform’, ‘content’, and ‘digital’ appeared, it was found that youth’s sustainable fashion consumption must be related to digital such as online platforms. And the four clusters extracted through data clustering using semantic network and CONCOR analysis are ‘production and consumption that practices eco-friendly and ethical values,’ ‘future education that considers the sustainability of people and the earth,’ and ‘expansion of the digital market and They were the ‘Forecast’ and ‘Changes due to Corona’ groups. In this regard, it can be seen that this suggests that we need to consider the direction and method of educating youth on sustainable fashion consumption.